Namespaces
	detail

	fisheye

	flann

	gpu

	linemod

	ocl

	of2

	ogl

	RenderMode
	render mode

	superres

	videostab

Classes
class	_InputArray

class	_OutputArray

struct	Accumulator

struct	Accumulator< char >

struct	Accumulator< short >

struct	Accumulator< unsigned char >

struct	Accumulator< unsigned short >

class	AdjusterAdapter
	A feature detector parameter adjuster, this is used by the DynamicAdaptedFeatureDetector and is a wrapper for FeatureDetector that allow them to be adjusted after a detection. More...

class	Affine3

class	Algorithm

class	AlgorithmInfo

class	Allocator

class	AutoBuffer

class	AutoLock

class	BackgroundSubtractor

class	BackgroundSubtractorGMG

class	BackgroundSubtractorMOG

class	BackgroundSubtractorMOG2

class	BaseColumnFilter

class	BaseFilter

struct	BaseKeypoint

class	BaseRowFilter

class	BFMatcher

class	BlockedRange

class	BOWImgDescriptorExtractor

class	BOWKMeansTrainer

class	BOWTrainer

class	BriefDescriptorExtractor

class	BRISK

class	BruteForceMatcher

class	CalonderDescriptorExtractor

class	CascadeClassifier

class	CLAHE

class	CommandLineParser

class	Complex

class	CompressedRectilinearPortraitWarper

class	CompressedRectilinearWarper

class	CvAffinePose

class	CvFeatureTracker

struct	CvFeatureTrackerParams

class	CvHybridTracker

struct	CvHybridTrackerParams

class	CvMeanShiftTracker

struct	CvMeanShiftTrackerParams

struct	CvMotionModel

class	CylindricalWarper

class	CylindricalWarperGpu

class	DataDepth

class	DataDepth< _Tp * >

class	DataDepth< bool >

class	DataDepth< char >

class	DataDepth< double >

class	DataDepth< float >

class	DataDepth< int >

class	DataDepth< schar >

class	DataDepth< short >

class	DataDepth< uchar >

class	DataDepth< unsigned >

class	DataDepth< ushort >

class	DataType

class	DataType< Affine3< _Tp > >

class	DataType< bool >

class	DataType< char >

class	DataType< Complex< _Tp > >

class	DataType< double >

class	DataType< float >

class	DataType< int >

class	DataType< Matx< _Tp, m, n > >

class	DataType< Point3_< _Tp > >

class	DataType< Point_< _Tp > >

class	DataType< Range >

class	DataType< Rect_< _Tp > >

class	DataType< Scalar_< _Tp > >

class	DataType< schar >

class	DataType< short >

class	DataType< Size_< _Tp > >

class	DataType< std::complex< _Tp > >

class	DataType< uchar >

class	DataType< ushort >

class	DataType< Vec< _Tp, cn > >

class	DenseFeatureDetector

class	DenseOpticalFlow

class	DescriptorExtractor

class	DescriptorMatcher

struct	DetectionROI

class	Directory

struct	DMatch

struct	DrawMatchesFlags

class	DynamicAdaptedFeatureDetector
	an adaptively adjusting detector that iteratively detects until the desired number of features are detected. Beware that this is not thread safe - as the adjustment of parameters breaks the const of the detection routine... /TODO Make this const correct and thread safe More...

class	EM

class	Exception

class	FaceRecognizer

class	FastAdjuster
	an adjust for the FAST detector. This will basically decrement or increment the threshold by 1 More...

class	FastFeatureDetector

class	Feature2D

class	FeatureDetector

class	FeatureEvaluator

class	FernClassifier

class	FernDescriptorMatcher

class	FileNode

class	FileNodeIterator

class	FileStorage

class	FilterEngine

class	FisheyeWarper

class	FlannBasedMatcher

struct	Formatted

class	Formatter

class	FREAK

class	GeneralizedHough

class	GenericDescriptorMatcher

class	GFTTDetector

class	GlArrays
	OpenGL Arrays. More...

class	GlBuffer
	Smart pointer for OpenGL buffer memory with reference counting. More...

class	GlCamera
	OpenGL camera. More...

class	GlFont
	OpenGL Font. More...

class	GlTexture
	Smart pointer for OpenGL 2d texture memory with reference counting. More...

class	GreaterEq

class	GreaterEqIdx

class	GridAdaptedFeatureDetector

struct	Hamming

struct	HammingMultilevel

struct	HOGDescriptor

class	KalmanFilter

class	KDTree

class	KeyPoint

class	KeyPointsFilter

struct	L1

struct	L2

class	LatentSvmDetector

class	LDA

class	LDetector

class	LessThan

class	LessThanIdx

class	LevMarqSparse

class	LineIterator

class	LogPolar_Adjacent

class	LogPolar_Interp

class	LogPolar_Overlapping

class	Mat

class	Mat_

class	MatAllocator

class	MatCommaInitializer_

class	MatConstIterator

class	MatConstIterator_

class	MatExpr

class	MatIterator_

class	MatOp

class	MatOp_Iter_

class	Matx

struct	Matx_AddOp

struct	Matx_DetOp

struct	Matx_DetOp< _Tp, 1 >

struct	Matx_DetOp< _Tp, 2 >

struct	Matx_DetOp< _Tp, 3 >

struct	Matx_FastInvOp

struct	Matx_FastInvOp< _Tp, 2 >

struct	Matx_FastInvOp< _Tp, 3 >

struct	Matx_FastSolveOp

struct	Matx_FastSolveOp< _Tp, 2, 1 >

struct	Matx_FastSolveOp< _Tp, 3, 1 >

struct	Matx_MatMulOp

struct	Matx_MulOp

struct	Matx_ScaleOp

struct	Matx_SubOp

struct	Matx_TOp

class	MatxCommaInitializer

class	MercatorWarper

class	Mesh3D

class	Moments
	raster image moments More...

class	MSER

class	Mutex

class	NAryMatIterator

class	Octree

class	OneWayDescriptor

class	OneWayDescriptorBase

class	OneWayDescriptorMatcher

class	OneWayDescriptorObject

class	OpponentColorDescriptorExtractor

class	ORB

class	PaniniPortraitWarper

class	PaniniWarper

class	ParallelLoopBody

struct	Param

struct	ParamType

struct	ParamType< Algorithm >

struct	ParamType< bool >

struct	ParamType< double >

struct	ParamType< float >

struct	ParamType< int >

struct	ParamType< Mat >

struct	ParamType< short >

struct	ParamType< string >

struct	ParamType< uchar >

struct	ParamType< uint64 >

struct	ParamType< unsigned >

struct	ParamType< vector< Mat > >

class	PatchGenerator

class	PCA

class	PlanarObjectDetector

class	PlaneWarper

class	PlaneWarperGpu

class	Point3_

class	Point_

class	Ptr

class	PyramidAdaptedFeatureDetector

class	RandomizedTree

class	Range

class	Rect_

class	Retina

class	RNG

class	RNG_MT19937

class	RotatedRect

class	RTreeClassifier

struct	RTreeNode

struct	RTTIImpl

class	Scalar_

class	SelfSimDescriptor

class	Seq

class	SeqIterator

class	SIFT

class	SimilarRects

class	SimpleBlobDetector

class	Size_

struct	SL2

class	SparseMat

class	SparseMat_

class	SparseMatConstIterator

class	SparseMatConstIterator_

class	SparseMatIterator

class	SparseMatIterator_

class	SphericalWarper

class	SphericalWarperGpu

class	SpinImageModel

class	Split

class	StarAdjuster

class	StarDetector

class	StereoBM

class	StereographicWarper

class	StereoSGBM

class	StereoVar

class	Stitcher

class	Subdiv2D

class	SURF

class	SurfAdjuster

class	SVD

class	TermCriteria

class	TickMeter

class	TLSData

class	TLSDataContainer

class	TransverseMercatorWarper

class	Vec

class	VecCommaInitializer

class	VecReaderProxy

class	VecReaderProxy< _Tp, 1 >

class	Vector

class	VectorDescriptorMatcher

class	VecWriterProxy

class	VecWriterProxy< _Tp, 1 >

class	VideoCapture

class	VideoWriter

class	WarperCreator

class	WImage

class	WImageBuffer

class	WImageBufferC

class	WImageC

class	WImageView

class	WImageViewC

class	WriteStructContext

Typedefs
typedef Affine3< float >	Affine3f

typedef Affine3< double >	Affine3d

typedef std::vector< Rect >	ConcurrentRectVector

typedef std::vector< double >	ConcurrentDoubleVector

typedef std::string	String

typedef Mat	MatND

typedef std::basic_string< wchar_t >	WString

typedef int(CV_CDECL *	ErrorCallback) (int status, const char func_name, const char err_msg, const char file_name, int line, void userdata)

typedef Matx< float, 1, 2 >	Matx12f

typedef Matx< double, 1, 2 >	Matx12d

typedef Matx< float, 1, 3 >	Matx13f

typedef Matx< double, 1, 3 >	Matx13d

typedef Matx< float, 1, 4 >	Matx14f

typedef Matx< double, 1, 4 >	Matx14d

typedef Matx< float, 1, 6 >	Matx16f

typedef Matx< double, 1, 6 >	Matx16d

typedef Matx< float, 2, 1 >	Matx21f

typedef Matx< double, 2, 1 >	Matx21d

typedef Matx< float, 3, 1 >	Matx31f

typedef Matx< double, 3, 1 >	Matx31d

typedef Matx< float, 4, 1 >	Matx41f

typedef Matx< double, 4, 1 >	Matx41d

typedef Matx< float, 6, 1 >	Matx61f

typedef Matx< double, 6, 1 >	Matx61d

typedef Matx< float, 2, 2 >	Matx22f

typedef Matx< double, 2, 2 >	Matx22d

typedef Matx< float, 2, 3 >	Matx23f

typedef Matx< double, 2, 3 >	Matx23d

typedef Matx< float, 3, 2 >	Matx32f

typedef Matx< double, 3, 2 >	Matx32d

typedef Matx< float, 3, 3 >	Matx33f

typedef Matx< double, 3, 3 >	Matx33d

typedef Matx< float, 3, 4 >	Matx34f

typedef Matx< double, 3, 4 >	Matx34d

typedef Matx< float, 4, 3 >	Matx43f

typedef Matx< double, 4, 3 >	Matx43d

typedef Matx< float, 4, 4 >	Matx44f

typedef Matx< double, 4, 4 >	Matx44d

typedef Matx< float, 6, 6 >	Matx66f

typedef Matx< double, 6, 6 >	Matx66d

typedef Vec< uchar, 2 >	Vec2b

typedef Vec< uchar, 3 >	Vec3b

typedef Vec< uchar, 4 >	Vec4b

typedef Vec< short, 2 >	Vec2s

typedef Vec< short, 3 >	Vec3s

typedef Vec< short, 4 >	Vec4s

typedef Vec< ushort, 2 >	Vec2w

typedef Vec< ushort, 3 >	Vec3w

typedef Vec< ushort, 4 >	Vec4w

typedef Vec< int, 2 >	Vec2i

typedef Vec< int, 3 >	Vec3i

typedef Vec< int, 4 >	Vec4i

typedef Vec< int, 6 >	Vec6i

typedef Vec< int, 8 >	Vec8i

typedef Vec< float, 2 >	Vec2f

typedef Vec< float, 3 >	Vec3f

typedef Vec< float, 4 >	Vec4f

typedef Vec< float, 6 >	Vec6f

typedef Vec< double, 2 >	Vec2d

typedef Vec< double, 3 >	Vec3d

typedef Vec< double, 4 >	Vec4d

typedef Vec< double, 6 >	Vec6d

typedef Complex< float >	Complexf

typedef Complex< double >	Complexd

typedef Point_< int >	Point2i

typedef Point_< int64 >	Point2l

typedef Point2i	Point

typedef Size_< int >	Size2i

typedef Size_< int64 >	Size2l

typedef Size_< double >	Size2d

typedef Size2i	Size

typedef Rect_< int >	Rect

typedef Point_< float >	Point2f

typedef Point_< double >	Point2d

typedef Size_< float >	Size2f

typedef Point3_< int >	Point3i

typedef Point3_< float >	Point3f

typedef Point3_< double >	Point3d

typedef Scalar_< double >	Scalar

typedef const _InputArray &	InputArray

typedef InputArray	InputArrayOfArrays

typedef const _OutputArray &	OutputArray

typedef OutputArray	OutputArrayOfArrays

typedef OutputArray	InputOutputArray

typedef OutputArray	InputOutputArrayOfArrays

typedef void(*	BinaryFunc) (const uchar src1, size_t step1, const uchar src2, size_t step2, uchar dst, size_t step, Size sz, void )

typedef Mat_< uchar >	Mat1b

typedef Mat_< Vec2b >	Mat2b

typedef Mat_< Vec3b >	Mat3b

typedef Mat_< Vec4b >	Mat4b

typedef Mat_< short >	Mat1s

typedef Mat_< Vec2s >	Mat2s

typedef Mat_< Vec3s >	Mat3s

typedef Mat_< Vec4s >	Mat4s

typedef Mat_< ushort >	Mat1w

typedef Mat_< Vec2w >	Mat2w

typedef Mat_< Vec3w >	Mat3w

typedef Mat_< Vec4w >	Mat4w

typedef Mat_< int >	Mat1i

typedef Mat_< Vec2i >	Mat2i

typedef Mat_< Vec3i >	Mat3i

typedef Mat_< Vec4i >	Mat4i

typedef Mat_< float >	Mat1f

typedef Mat_< Vec2f >	Mat2f

typedef Mat_< Vec3f >	Mat3f

typedef Mat_< Vec4f >	Mat4f

typedef Mat_< double >	Mat1d

typedef Mat_< Vec2d >	Mat2d

typedef Mat_< Vec3d >	Mat3d

typedef Mat_< Vec4d >	Mat4d

typedef void(*	ConvertData) (const void from, void to, int cn)

typedef void(*	ConvertScaleData) (const void from, void to, int cn, double alpha, double beta)

typedef Ptr< CvMemStorage >	MemStorage

typedef WImage< uchar >	WImage_b

typedef WImageView< uchar >	WImageView_b

typedef WImageBuffer< uchar >	WImageBuffer_b

typedef WImageC< uchar, 1 >	WImage1_b

typedef WImageViewC< uchar, 1 >	WImageView1_b

typedef WImageBufferC< uchar, 1 >	WImageBuffer1_b

typedef WImageC< uchar, 3 >	WImage3_b

typedef WImageViewC< uchar, 3 >	WImageView3_b

typedef WImageBufferC< uchar, 3 >	WImageBuffer3_b

typedef WImage< float >	WImage_f

typedef WImageView< float >	WImageView_f

typedef WImageBuffer< float >	WImageBuffer_f

typedef WImageC< float, 1 >	WImage1_f

typedef WImageViewC< float, 1 >	WImageView1_f

typedef WImageBufferC< float, 1 >	WImageBuffer1_f

typedef WImageC< float, 3 >	WImage3_f

typedef WImageViewC< float, 3 >	WImageView3_f

typedef WImageBufferC< float, 3 >	WImageBuffer3_f

typedef WImage< short >	WImage_16s

typedef WImageView< short >	WImageView_16s

typedef WImageBuffer< short >	WImageBuffer_16s

typedef WImageC< short, 1 >	WImage1_16s

typedef WImageViewC< short, 1 >	WImageView1_16s

typedef WImageBufferC< short, 1 >	WImageBuffer1_16s

typedef WImageC< short, 3 >	WImage3_16s

typedef WImageViewC< short, 3 >	WImageView3_16s

typedef WImageBufferC< short, 3 >	WImageBuffer3_16s

typedef WImage< ushort >	WImage_16u

typedef WImageView< ushort >	WImageView_16u

typedef WImageBuffer< ushort >	WImageBuffer_16u

typedef WImageC< ushort, 1 >	WImage1_16u

typedef WImageViewC< ushort, 1 >	WImageView1_16u

typedef WImageBufferC< ushort, 1 >	WImageBuffer1_16u

typedef WImageC< ushort, 3 >	WImage3_16u

typedef WImageViewC< ushort, 3 >	WImageView3_16u

typedef WImageBufferC< ushort, 3 >	WImageBuffer3_16u

typedef void(*	MouseCallback) (int event, int x, int y, int flags, void *userdata)

typedef void(CV_CDECL *	TrackbarCallback) (int pos, void *userdata)

typedef void(*	OpenGlDrawCallback) (void *userdata)

typedef void(CV_CDECL *	ButtonCallback) (int state, void *userdata)

typedef ORB	OrbFeatureDetector

typedef ORB	OrbDescriptorExtractor

typedef MSER	MserFeatureDetector

typedef GFTTDetector	GoodFeaturesToTrackDetector

typedef StarDetector	StarFeatureDetector

typedef Hamming	HammingLUT

typedef GenericDescriptorMatcher	GenericDescriptorMatch

typedef VectorDescriptorMatcher	VectorDescriptorMatch

typedef CvStatModel	StatModel

typedef CvParamGrid	ParamGrid

typedef CvNormalBayesClassifier	NormalBayesClassifier

typedef CvKNearest	KNearest

typedef CvSVMParams	SVMParams

typedef CvSVMKernel	SVMKernel

typedef CvSVMSolver	SVMSolver

typedef CvSVM	SVM

typedef CvDTreeParams	DTreeParams

typedef CvMLData	TrainData

typedef CvDTree	DecisionTree

typedef CvForestTree	ForestTree

typedef CvRTParams	RandomTreeParams

typedef CvRTrees	RandomTrees

typedef CvERTreeTrainData	ERTreeTRainData

typedef CvForestERTree	ERTree

typedef CvERTrees	ERTrees

typedef CvBoostParams	BoostParams

typedef CvBoostTree	BoostTree

typedef CvBoost	Boost

typedef CvANN_MLP_TrainParams	ANN_MLP_TrainParams

typedef CvANN_MLP	NeuralNet_MLP

typedef CvGBTreesParams	GradientBoostingTreeParams

typedef CvGBTrees	GradientBoostingTrees

typedef SIFT	SiftFeatureDetector

typedef SIFT	SiftDescriptorExtractor

typedef SURF	SurfFeatureDetector

typedef SURF	SurfDescriptorExtractor

typedef CvMotionModel	MotionModel

typedef CvMeanShiftTrackerParams	MeanShiftTrackerParams

typedef CvFeatureTrackerParams	FeatureTrackerParams

typedef CvHybridTrackerParams	HybridTrackerParams

typedef CvMeanShiftTracker	MeanShiftTracker

typedef CvFeatureTracker	FeatureTracker

typedef CvHybridTracker	HybridTracker

typedef bool(*	BundleAdjustCallback) (int iteration, double norm_error, void *user_data)

typedef CvEMParams	EMParams

typedef CvEM	ExpectationMaximization

typedef LDetector	YAPE

typedef OneWayDescriptorMatcher	OneWayDescriptorMatch

typedef FernDescriptorMatcher	FernDescriptorMatch

Enumerations
enum	{ DECOMP_LU =0, DECOMP_SVD =1, DECOMP_EIG =2, DECOMP_CHOLESKY =3, DECOMP_QR =4, DECOMP_NORMAL =16 }

enum	{ NORM_INF =1, NORM_L1 =2, NORM_L2 =4, NORM_L2SQR =5, NORM_HAMMING =6, NORM_HAMMING2 =7, NORM_TYPE_MASK =7, NORM_RELATIVE =8, NORM_MINMAX =32 }

enum	{ CMP_EQ =0, CMP_GT =1, CMP_GE =2, CMP_LT =3, CMP_LE =4, CMP_NE =5 }

enum	{ GEMM_1_T =1, GEMM_2_T =2, GEMM_3_T =4 }

enum	{ DFT_INVERSE =1, DFT_SCALE =2, DFT_ROWS =4, DFT_COMPLEX_OUTPUT =16, DFT_REAL_OUTPUT =32, DCT_INVERSE = DFT_INVERSE, DCT_ROWS =DFT_ROWS }

enum	{ DEPTH_MASK_8U = 1 << CV_8U, DEPTH_MASK_8S = 1 << CV_8S, DEPTH_MASK_16U = 1 << CV_16U, DEPTH_MASK_16S = 1 << CV_16S, DEPTH_MASK_32S = 1 << CV_32S, DEPTH_MASK_32F = 1 << CV_32F, DEPTH_MASK_64F = 1 << CV_64F, DEPTH_MASK_ALL = (DEPTH_MASK_64F<<1)-1, DEPTH_MASK_ALL_BUT_8S = DEPTH_MASK_ALL & ~DEPTH_MASK_8S, DEPTH_MASK_FLT = DEPTH_MASK_32F + DEPTH_MASK_64F }

enum	{ MAGIC_MASK =0xFFFF0000, TYPE_MASK =0x00000FFF, DEPTH_MASK =7 }

enum	{ SORT_EVERY_ROW =0, SORT_EVERY_COLUMN =1, SORT_ASCENDING =0, SORT_DESCENDING =16 }

enum	{ COVAR_SCRAMBLED =0, COVAR_NORMAL =1, COVAR_USE_AVG =2, COVAR_SCALE =4, COVAR_ROWS =8, COVAR_COLS =16 }

enum	{ KMEANS_RANDOM_CENTERS =0, KMEANS_PP_CENTERS =2, KMEANS_USE_INITIAL_LABELS =1 }

enum	MarkerTypes { MARKER_CROSS = 0, MARKER_TILTED_CROSS = 1, MARKER_STAR = 2, MARKER_DIAMOND = 3, MARKER_SQUARE = 4, MARKER_TRIANGLE_UP = 5, MARKER_TRIANGLE_DOWN = 6 }
	Possible set of marker types used for the drawMarker function. More...

enum	{ FONT_HERSHEY_SIMPLEX = 0, FONT_HERSHEY_PLAIN = 1, FONT_HERSHEY_DUPLEX = 2, FONT_HERSHEY_COMPLEX = 3, FONT_HERSHEY_TRIPLEX = 4, FONT_HERSHEY_COMPLEX_SMALL = 5, FONT_HERSHEY_SCRIPT_SIMPLEX = 6, FONT_HERSHEY_SCRIPT_COMPLEX = 7, FONT_ITALIC = 16 }

enum	{ BORDER_REPLICATE =IPL_BORDER_REPLICATE, BORDER_CONSTANT =IPL_BORDER_CONSTANT, BORDER_REFLECT =IPL_BORDER_REFLECT, BORDER_WRAP =IPL_BORDER_WRAP, BORDER_REFLECT_101 =IPL_BORDER_REFLECT_101, BORDER_REFLECT101 =BORDER_REFLECT_101, BORDER_TRANSPARENT =IPL_BORDER_TRANSPARENT, BORDER_DEFAULT =BORDER_REFLECT_101, BORDER_ISOLATED =16 }
	various border interpolation methods More...

enum	{ KERNEL_GENERAL =0, KERNEL_SYMMETRICAL =1, KERNEL_ASYMMETRICAL =2, KERNEL_SMOOTH =4, KERNEL_INTEGER =8 }
	type of the kernel More...

enum	{ MORPH_ERODE =CV_MOP_ERODE, MORPH_DILATE =CV_MOP_DILATE, MORPH_OPEN =CV_MOP_OPEN, MORPH_CLOSE =CV_MOP_CLOSE, MORPH_GRADIENT =CV_MOP_GRADIENT, MORPH_TOPHAT =CV_MOP_TOPHAT, MORPH_BLACKHAT =CV_MOP_BLACKHAT, MORPH_HITMISS }
	type of morphological operation More...

enum	{ MORPH_RECT =0, MORPH_CROSS =1, MORPH_ELLIPSE =2 }
	shape of the structuring element More...

enum	{ GHT_POSITION = 0, GHT_SCALE = 1, GHT_ROTATION = 2 }

enum	{ INTER_NEAREST =CV_INTER_NN, INTER_LINEAR =CV_INTER_LINEAR, INTER_CUBIC =CV_INTER_CUBIC, INTER_AREA =CV_INTER_AREA, INTER_LANCZOS4 =CV_INTER_LANCZOS4, INTER_MAX =7, WARP_INVERSE_MAP =CV_WARP_INVERSE_MAP }
	interpolation algorithm More...

enum	{ INTER_BITS =5, INTER_BITS2 =INTER_BITS2, INTER_TAB_SIZE =(1<<INTER_BITS), INTER_TAB_SIZE2 =INTER_TAB_SIZEINTER_TAB_SIZE }

enum	{ THRESH_BINARY =CV_THRESH_BINARY, THRESH_BINARY_INV =CV_THRESH_BINARY_INV, THRESH_TRUNC =CV_THRESH_TRUNC, THRESH_TOZERO =CV_THRESH_TOZERO, THRESH_TOZERO_INV =CV_THRESH_TOZERO_INV, THRESH_MASK =CV_THRESH_MASK, THRESH_OTSU =CV_THRESH_OTSU }
	type of the threshold operation More...

enum	{ ADAPTIVE_THRESH_MEAN_C =0, ADAPTIVE_THRESH_GAUSSIAN_C =1 }
	adaptive threshold algorithm More...

enum	{ PROJ_SPHERICAL_ORTHO = 0, PROJ_SPHERICAL_EQRECT = 1 }

enum	{ GC_BGD = 0, GC_FGD = 1, GC_PR_BGD = 2, GC_PR_FGD = 3 }
	class of the pixel in GrabCut algorithm More...

enum	{ GC_INIT_WITH_RECT = 0, GC_INIT_WITH_MASK = 1, GC_EVAL = 2 }
	GrabCut algorithm flags. More...

enum	{ DIST_LABEL_CCOMP = 0, DIST_LABEL_PIXEL = 1 }

enum	{ FLOODFILL_FIXED_RANGE = 1 << 16, FLOODFILL_MASK_ONLY = 1 << 17 }

enum	{ COLOR_BGR2BGRA =0, COLOR_RGB2RGBA =COLOR_BGR2BGRA, COLOR_BGRA2BGR =1, COLOR_RGBA2RGB =COLOR_BGRA2BGR, COLOR_BGR2RGBA =2, COLOR_RGB2BGRA =COLOR_BGR2RGBA, COLOR_RGBA2BGR =3, COLOR_BGRA2RGB =COLOR_RGBA2BGR, COLOR_BGR2RGB =4, COLOR_RGB2BGR =COLOR_BGR2RGB, COLOR_BGRA2RGBA =5, COLOR_RGBA2BGRA =COLOR_BGRA2RGBA, COLOR_BGR2GRAY =6, COLOR_RGB2GRAY =7, COLOR_GRAY2BGR =8, COLOR_GRAY2RGB =COLOR_GRAY2BGR, COLOR_GRAY2BGRA =9, COLOR_GRAY2RGBA =COLOR_GRAY2BGRA, COLOR_BGRA2GRAY =10, COLOR_RGBA2GRAY =11, COLOR_BGR2BGR565 =12, COLOR_RGB2BGR565 =13, COLOR_BGR5652BGR =14, COLOR_BGR5652RGB =15, COLOR_BGRA2BGR565 =16, COLOR_RGBA2BGR565 =17, COLOR_BGR5652BGRA =18, COLOR_BGR5652RGBA =19, COLOR_GRAY2BGR565 =20, COLOR_BGR5652GRAY =21, COLOR_BGR2BGR555 =22, COLOR_RGB2BGR555 =23, COLOR_BGR5552BGR =24, COLOR_BGR5552RGB =25, COLOR_BGRA2BGR555 =26, COLOR_RGBA2BGR555 =27, COLOR_BGR5552BGRA =28, COLOR_BGR5552RGBA =29, COLOR_GRAY2BGR555 =30, COLOR_BGR5552GRAY =31, COLOR_BGR2XYZ =32, COLOR_RGB2XYZ =33, COLOR_XYZ2BGR =34, COLOR_XYZ2RGB =35, COLOR_BGR2YCrCb =36, COLOR_RGB2YCrCb =37, COLOR_YCrCb2BGR =38, COLOR_YCrCb2RGB =39, COLOR_BGR2HSV =40, COLOR_RGB2HSV =41, COLOR_BGR2Lab =44, COLOR_RGB2Lab =45, COLOR_BayerBG2BGR =46, COLOR_BayerGB2BGR =47, COLOR_BayerRG2BGR =48, COLOR_BayerGR2BGR =49, COLOR_BayerBG2RGB =COLOR_BayerRG2BGR, COLOR_BayerGB2RGB =COLOR_BayerGR2BGR, COLOR_BayerRG2RGB =COLOR_BayerBG2BGR, COLOR_BayerGR2RGB =COLOR_BayerGB2BGR, COLOR_BGR2Luv =50, COLOR_RGB2Luv =51, COLOR_BGR2HLS =52, COLOR_RGB2HLS =53, COLOR_HSV2BGR =54, COLOR_HSV2RGB =55, COLOR_Lab2BGR =56, COLOR_Lab2RGB =57, COLOR_Luv2BGR =58, COLOR_Luv2RGB =59, COLOR_HLS2BGR =60, COLOR_HLS2RGB =61, COLOR_BayerBG2BGR_VNG =62, COLOR_BayerGB2BGR_VNG =63, COLOR_BayerRG2BGR_VNG =64, COLOR_BayerGR2BGR_VNG =65, COLOR_BayerBG2RGB_VNG =COLOR_BayerRG2BGR_VNG, COLOR_BayerGB2RGB_VNG =COLOR_BayerGR2BGR_VNG, COLOR_BayerRG2RGB_VNG =COLOR_BayerBG2BGR_VNG, COLOR_BayerGR2RGB_VNG =COLOR_BayerGB2BGR_VNG, COLOR_BGR2HSV_FULL = 66, COLOR_RGB2HSV_FULL = 67, COLOR_BGR2HLS_FULL = 68, COLOR_RGB2HLS_FULL = 69, COLOR_HSV2BGR_FULL = 70, COLOR_HSV2RGB_FULL = 71, COLOR_HLS2BGR_FULL = 72, COLOR_HLS2RGB_FULL = 73, COLOR_LBGR2Lab = 74, COLOR_LRGB2Lab = 75, COLOR_LBGR2Luv = 76, COLOR_LRGB2Luv = 77, COLOR_Lab2LBGR = 78, COLOR_Lab2LRGB = 79, COLOR_Luv2LBGR = 80, COLOR_Luv2LRGB = 81, COLOR_BGR2YUV = 82, COLOR_RGB2YUV = 83, COLOR_YUV2BGR = 84, COLOR_YUV2RGB = 85, COLOR_BayerBG2GRAY = 86, COLOR_BayerGB2GRAY = 87, COLOR_BayerRG2GRAY = 88, COLOR_BayerGR2GRAY = 89, COLOR_YUV2RGB_NV12 = 90, COLOR_YUV2BGR_NV12 = 91, COLOR_YUV2RGB_NV21 = 92, COLOR_YUV2BGR_NV21 = 93, COLOR_YUV420sp2RGB = COLOR_YUV2RGB_NV21, COLOR_YUV420sp2BGR = COLOR_YUV2BGR_NV21, COLOR_YUV2RGBA_NV12 = 94, COLOR_YUV2BGRA_NV12 = 95, COLOR_YUV2RGBA_NV21 = 96, COLOR_YUV2BGRA_NV21 = 97, COLOR_YUV420sp2RGBA = COLOR_YUV2RGBA_NV21, COLOR_YUV420sp2BGRA = COLOR_YUV2BGRA_NV21, COLOR_YUV2RGB_YV12 = 98, COLOR_YUV2BGR_YV12 = 99, COLOR_YUV2RGB_IYUV = 100, COLOR_YUV2BGR_IYUV = 101, COLOR_YUV2RGB_I420 = COLOR_YUV2RGB_IYUV, COLOR_YUV2BGR_I420 = COLOR_YUV2BGR_IYUV, COLOR_YUV420p2RGB = COLOR_YUV2RGB_YV12, COLOR_YUV420p2BGR = COLOR_YUV2BGR_YV12, COLOR_YUV2RGBA_YV12 = 102, COLOR_YUV2BGRA_YV12 = 103, COLOR_YUV2RGBA_IYUV = 104, COLOR_YUV2BGRA_IYUV = 105, COLOR_YUV2RGBA_I420 = COLOR_YUV2RGBA_IYUV, COLOR_YUV2BGRA_I420 = COLOR_YUV2BGRA_IYUV, COLOR_YUV420p2RGBA = COLOR_YUV2RGBA_YV12, COLOR_YUV420p2BGRA = COLOR_YUV2BGRA_YV12, COLOR_YUV2GRAY_420 = 106, COLOR_YUV2GRAY_NV21 = COLOR_YUV2GRAY_420, COLOR_YUV2GRAY_NV12 = COLOR_YUV2GRAY_420, COLOR_YUV2GRAY_YV12 = COLOR_YUV2GRAY_420, COLOR_YUV2GRAY_IYUV = COLOR_YUV2GRAY_420, COLOR_YUV2GRAY_I420 = COLOR_YUV2GRAY_420, COLOR_YUV420sp2GRAY = COLOR_YUV2GRAY_420, COLOR_YUV420p2GRAY = COLOR_YUV2GRAY_420, COLOR_YUV2RGB_UYVY = 107, COLOR_YUV2BGR_UYVY = 108, COLOR_YUV2RGB_Y422 = COLOR_YUV2RGB_UYVY, COLOR_YUV2BGR_Y422 = COLOR_YUV2BGR_UYVY, COLOR_YUV2RGB_UYNV = COLOR_YUV2RGB_UYVY, COLOR_YUV2BGR_UYNV = COLOR_YUV2BGR_UYVY, COLOR_YUV2RGBA_UYVY = 111, COLOR_YUV2BGRA_UYVY = 112, COLOR_YUV2RGBA_Y422 = COLOR_YUV2RGBA_UYVY, COLOR_YUV2BGRA_Y422 = COLOR_YUV2BGRA_UYVY, COLOR_YUV2RGBA_UYNV = COLOR_YUV2RGBA_UYVY, COLOR_YUV2BGRA_UYNV = COLOR_YUV2BGRA_UYVY, COLOR_YUV2RGB_YUY2 = 115, COLOR_YUV2BGR_YUY2 = 116, COLOR_YUV2RGB_YVYU = 117, COLOR_YUV2BGR_YVYU = 118, COLOR_YUV2RGB_YUYV = COLOR_YUV2RGB_YUY2, COLOR_YUV2BGR_YUYV = COLOR_YUV2BGR_YUY2, COLOR_YUV2RGB_YUNV = COLOR_YUV2RGB_YUY2, COLOR_YUV2BGR_YUNV = COLOR_YUV2BGR_YUY2, COLOR_YUV2RGBA_YUY2 = 119, COLOR_YUV2BGRA_YUY2 = 120, COLOR_YUV2RGBA_YVYU = 121, COLOR_YUV2BGRA_YVYU = 122, COLOR_YUV2RGBA_YUYV = COLOR_YUV2RGBA_YUY2, COLOR_YUV2BGRA_YUYV = COLOR_YUV2BGRA_YUY2, COLOR_YUV2RGBA_YUNV = COLOR_YUV2RGBA_YUY2, COLOR_YUV2BGRA_YUNV = COLOR_YUV2BGRA_YUY2, COLOR_YUV2GRAY_UYVY = 123, COLOR_YUV2GRAY_YUY2 = 124, COLOR_YUV2GRAY_Y422 = COLOR_YUV2GRAY_UYVY, COLOR_YUV2GRAY_UYNV = COLOR_YUV2GRAY_UYVY, COLOR_YUV2GRAY_YVYU = COLOR_YUV2GRAY_YUY2, COLOR_YUV2GRAY_YUYV = COLOR_YUV2GRAY_YUY2, COLOR_YUV2GRAY_YUNV = COLOR_YUV2GRAY_YUY2, COLOR_RGBA2mRGBA = 125, COLOR_mRGBA2RGBA = 126, COLOR_RGB2YUV_I420 = 127, COLOR_BGR2YUV_I420 = 128, COLOR_RGB2YUV_IYUV = COLOR_RGB2YUV_I420, COLOR_BGR2YUV_IYUV = COLOR_BGR2YUV_I420, COLOR_RGBA2YUV_I420 = 129, COLOR_BGRA2YUV_I420 = 130, COLOR_RGBA2YUV_IYUV = COLOR_RGBA2YUV_I420, COLOR_BGRA2YUV_IYUV = COLOR_BGRA2YUV_I420, COLOR_RGB2YUV_YV12 = 131, COLOR_BGR2YUV_YV12 = 132, COLOR_RGBA2YUV_YV12 = 133, COLOR_BGRA2YUV_YV12 = 134, COLOR_COLORCVT_MAX = 135 }

enum	{ TM_SQDIFF =0, TM_SQDIFF_NORMED =1, TM_CCORR =2, TM_CCORR_NORMED =3, TM_CCOEFF =4, TM_CCOEFF_NORMED =5 }
	type of the template matching operation More...

enum	{ RETR_EXTERNAL =CV_RETR_EXTERNAL, RETR_LIST =CV_RETR_LIST, RETR_CCOMP =CV_RETR_CCOMP, RETR_TREE =CV_RETR_TREE, RETR_FLOODFILL =CV_RETR_FLOODFILL }
	mode of the contour retrieval algorithm More...

enum	{ CHAIN_APPROX_NONE =CV_CHAIN_APPROX_NONE, CHAIN_APPROX_SIMPLE =CV_CHAIN_APPROX_SIMPLE, CHAIN_APPROX_TC89_L1 =CV_CHAIN_APPROX_TC89_L1, CHAIN_APPROX_TC89_KCOS =CV_CHAIN_APPROX_TC89_KCOS }
	the contour approximation algorithm More...

enum	{ WINDOW_NORMAL = CV_WINDOW_NORMAL, WINDOW_AUTOSIZE = CV_WINDOW_AUTOSIZE, WINDOW_OPENGL = CV_WINDOW_OPENGL, WND_PROP_FULLSCREEN = CV_WND_PROP_FULLSCREEN, WND_PROP_AUTOSIZE = CV_WND_PROP_AUTOSIZE, WND_PROP_ASPECT_RATIO = CV_WND_PROP_ASPECTRATIO, WND_PROP_OPENGL = CV_WND_PROP_OPENGL }

enum	{ EVENT_MOUSEMOVE =0, EVENT_LBUTTONDOWN =1, EVENT_RBUTTONDOWN =2, EVENT_MBUTTONDOWN =3, EVENT_LBUTTONUP =4, EVENT_RBUTTONUP =5, EVENT_MBUTTONUP =6, EVENT_LBUTTONDBLCLK =7, EVENT_RBUTTONDBLCLK =8, EVENT_MBUTTONDBLCLK =9 }

enum	{ EVENT_FLAG_LBUTTON =1, EVENT_FLAG_RBUTTON =2, EVENT_FLAG_MBUTTON =4, EVENT_FLAG_CTRLKEY =8, EVENT_FLAG_SHIFTKEY =16, EVENT_FLAG_ALTKEY =32 }

enum	{ IMREAD_UNCHANGED =-1, IMREAD_GRAYSCALE =0, IMREAD_COLOR =1, IMREAD_ANYDEPTH =2, IMREAD_ANYCOLOR =4 }

enum	{ IMWRITE_JPEG_QUALITY =1, IMWRITE_PNG_COMPRESSION =16, IMWRITE_PNG_STRATEGY =17, IMWRITE_PNG_BILEVEL =18, IMWRITE_PNG_STRATEGY_DEFAULT =0, IMWRITE_PNG_STRATEGY_FILTERED =1, IMWRITE_PNG_STRATEGY_HUFFMAN_ONLY =2, IMWRITE_PNG_STRATEGY_RLE =3, IMWRITE_PNG_STRATEGY_FIXED =4, IMWRITE_PXM_BINARY =32 }

enum	{ OPTFLOW_USE_INITIAL_FLOW = 4, OPTFLOW_LK_GET_MIN_EIGENVALS = 8, OPTFLOW_FARNEBACK_GAUSSIAN = 256 }

enum	{ LMEDS = 4, RANSAC = 8 }
	type of the robust estimation algorithm More...

enum	{ ITERATIVE =CV_ITERATIVE, EPNP =CV_EPNP, P3P =CV_P3P }
	computes the camera pose from a few 3D points and the corresponding projections. The outliers are not handled. More...

enum	{ CALIB_CB_ADAPTIVE_THRESH = 1, CALIB_CB_NORMALIZE_IMAGE = 2, CALIB_CB_FILTER_QUADS = 4, CALIB_CB_FAST_CHECK = 8 }

enum	{ CALIB_CB_SYMMETRIC_GRID = 1, CALIB_CB_ASYMMETRIC_GRID = 2, CALIB_CB_CLUSTERING = 4 }

enum	{ CALIB_USE_INTRINSIC_GUESS = 1, CALIB_FIX_ASPECT_RATIO = 2, CALIB_FIX_PRINCIPAL_POINT = 4, CALIB_ZERO_TANGENT_DIST = 8, CALIB_FIX_FOCAL_LENGTH = 16, CALIB_FIX_K1 = 32, CALIB_FIX_K2 = 64, CALIB_FIX_K3 = 128, CALIB_FIX_K4 = 2048, CALIB_FIX_K5 = 4096, CALIB_FIX_K6 = 8192, CALIB_RATIONAL_MODEL = 16384, CALIB_FIX_INTRINSIC = 256, CALIB_SAME_FOCAL_LENGTH = 512, CALIB_ZERO_DISPARITY = 1024 }

enum	{ FM_7POINT = 1, FM_8POINT = 2, FM_LMEDS = 4, FM_RANSAC = 8 }
	the algorithm for finding fundamental matrix More...

enum	{ CASCADE_DO_CANNY_PRUNING =1, CASCADE_SCALE_IMAGE =2, CASCADE_FIND_BIGGEST_OBJECT =4, CASCADE_DO_ROUGH_SEARCH =8 }

enum	{ INPAINT_NS =CV_INPAINT_NS, INPAINT_TELEA =CV_INPAINT_TELEA }
	the inpainting algorithm More...

enum	RETINA_COLORSAMPLINGMETHOD { RETINA_COLOR_RANDOM, RETINA_COLOR_DIAGONAL, RETINA_COLOR_BAYER }

enum	{ ROTATION = 1, TRANSLATION = 2, RIGID_BODY_MOTION = 4 }

enum	{ COLORMAP_AUTUMN = 0, COLORMAP_BONE = 1, COLORMAP_JET = 2, COLORMAP_WINTER = 3, COLORMAP_RAINBOW = 4, COLORMAP_OCEAN = 5, COLORMAP_SUMMER = 6, COLORMAP_SPRING = 7, COLORMAP_COOL = 8, COLORMAP_HSV = 9, COLORMAP_PINK = 10, COLORMAP_HOT = 11 }

Functions
template<typename _Tp , int _rows, int _cols, int _options, int _maxRows, int _maxCols>
void	eigen2cv (const Eigen::Matrix< _Tp, _rows, _cols, _options, _maxRows, _maxCols > &src, Mat &dst)

template<typename _Tp , int _rows, int _cols, int _options, int _maxRows, int _maxCols>
void	cv2eigen (const Mat &src, Eigen::Matrix< _Tp, _rows, _cols, _options, _maxRows, _maxCols > &dst)

template<typename _Tp , int _rows, int _cols, int _options, int _maxRows, int _maxCols>
void	cv2eigen (const Matx< _Tp, _rows, _cols > &src, Eigen::Matrix< _Tp, _rows, _cols, _options, _maxRows, _maxCols > &dst)

template<typename _Tp >
void	cv2eigen (const Mat &src, Eigen::Matrix< _Tp, Eigen::Dynamic, Eigen::Dynamic > &dst)

template<typename _Tp , int _rows, int _cols>
void	cv2eigen (const Matx< _Tp, _rows, _cols > &src, Eigen::Matrix< _Tp, Eigen::Dynamic, Eigen::Dynamic > &dst)

template<typename _Tp >
void	cv2eigen (const Mat &src, Eigen::Matrix< _Tp, Eigen::Dynamic, 1 > &dst)

template<typename _Tp , int _rows>
void	cv2eigen (const Matx< _Tp, _rows, 1 > &src, Eigen::Matrix< _Tp, Eigen::Dynamic, 1 > &dst)

template<typename _Tp >
void	cv2eigen (const Mat &src, Eigen::Matrix< _Tp, 1, Eigen::Dynamic > &dst)

template<typename _Tp , int _cols>
void	cv2eigen (const Matx< _Tp, 1, _cols > &src, Eigen::Matrix< _Tp, 1, Eigen::Dynamic > &dst)

const char *	currentParallelFramework ()

template<typename T1 , typename T2 , typename Op >
void	process (const Mat_< T1 > &m1, Mat_< T2 > &m2, Op op)

template<typename T1 , typename T2 , typename T3 , typename Op >
void	process (const Mat_< T1 > &m1, const Mat_< T2 > &m2, Mat_< T3 > &m3, Op op)

MatExpr	operator+ (const Mat &a, const Mat &b)

MatExpr	operator+ (const Mat &a, const Scalar &s)

MatExpr	operator+ (const Scalar &s, const Mat &a)

MatExpr	operator+ (const MatExpr &e, const Mat &m)

MatExpr	operator+ (const Mat &m, const MatExpr &e)

MatExpr	operator+ (const MatExpr &e, const Scalar &s)

MatExpr	operator+ (const Scalar &s, const MatExpr &e)

MatExpr	operator+ (const MatExpr &e1, const MatExpr &e2)

MatExpr	operator- (const Mat &a, const Mat &b)

MatExpr	operator- (const Mat &a, const Scalar &s)

MatExpr	operator- (const Scalar &s, const Mat &a)

MatExpr	operator- (const MatExpr &e, const Mat &m)

MatExpr	operator- (const Mat &m, const MatExpr &e)

MatExpr	operator- (const MatExpr &e, const Scalar &s)

MatExpr	operator- (const Scalar &s, const MatExpr &e)

MatExpr	operator- (const MatExpr &e1, const MatExpr &e2)

MatExpr	operator- (const Mat &m)

MatExpr	operator- (const MatExpr &e)

MatExpr	operator* (const Mat &a, const Mat &b)

MatExpr	operator* (const Mat &a, double s)

MatExpr	operator* (double s, const Mat &a)

MatExpr	operator* (const MatExpr &e, const Mat &m)

MatExpr	operator* (const Mat &m, const MatExpr &e)

MatExpr	operator* (const MatExpr &e, double s)

MatExpr	operator* (double s, const MatExpr &e)

MatExpr	operator* (const MatExpr &e1, const MatExpr &e2)

MatExpr	operator/ (const Mat &a, const Mat &b)

MatExpr	operator/ (const Mat &a, double s)

MatExpr	operator/ (double s, const Mat &a)

MatExpr	operator/ (const MatExpr &e, const Mat &m)

MatExpr	operator/ (const Mat &m, const MatExpr &e)

MatExpr	operator/ (const MatExpr &e, double s)

MatExpr	operator/ (double s, const MatExpr &e)

MatExpr	operator/ (const MatExpr &e1, const MatExpr &e2)

MatExpr	operator< (const Mat &a, const Mat &b)

MatExpr	operator< (const Mat &a, double s)

MatExpr	operator< (double s, const Mat &a)

MatExpr	operator<= (const Mat &a, const Mat &b)

MatExpr	operator<= (const Mat &a, double s)

MatExpr	operator<= (double s, const Mat &a)

MatExpr	operator== (const Mat &a, const Mat &b)

MatExpr	operator== (const Mat &a, double s)

MatExpr	operator== (double s, const Mat &a)

MatExpr	operator!= (const Mat &a, const Mat &b)

MatExpr	operator!= (const Mat &a, double s)

MatExpr	operator!= (double s, const Mat &a)

MatExpr	operator>= (const Mat &a, const Mat &b)

MatExpr	operator>= (const Mat &a, double s)

MatExpr	operator>= (double s, const Mat &a)

MatExpr	operator> (const Mat &a, const Mat &b)

MatExpr	operator> (const Mat &a, double s)

MatExpr	operator> (double s, const Mat &a)

MatExpr	min (const Mat &a, const Mat &b)

MatExpr	min (const Mat &a, double s)

MatExpr	min (double s, const Mat &a)

MatExpr	max (const Mat &a, const Mat &b)

MatExpr	max (const Mat &a, double s)

MatExpr	max (double s, const Mat &a)

MatExpr	operator& (const Mat &a, const Mat &b)

MatExpr	operator& (const Mat &a, const Scalar &s)

MatExpr	operator& (const Scalar &s, const Mat &a)

MatExpr	operator\| (const Mat &a, const Mat &b)

MatExpr	operator\| (const Mat &a, const Scalar &s)

MatExpr	operator\| (const Scalar &s, const Mat &a)

MatExpr	operator^ (const Mat &a, const Mat &b)

MatExpr	operator^ (const Mat &a, const Scalar &s)

MatExpr	operator^ (const Scalar &s, const Mat &a)

MatExpr	operator~ (const Mat &m)

MatExpr	abs (const Mat &m)

MatExpr	abs (const MatExpr &e)

template<typename _Tp >
void	split (const Mat &src, vector< Mat_< _Tp > > &mv)

ptrdiff_t	operator- (const MatConstIterator &b, const MatConstIterator &a)

void	render (const GlTexture &tex, Rect_< double > wndRect=Rect_< double >(0.0, 0.0, 1.0, 1.0), Rect_< double > texRect=Rect_< double >(0.0, 0.0, 1.0, 1.0))
	render functions More...

void	render (const GlArrays &arr, int mode=RenderMode::POINTS, Scalar color=Scalar::all(255))
	render OpenGL arrays More...

void	render (const std::string &str, const Ptr< GlFont > &font, Scalar color, Point2d pos)

string	fromUtf16 (const WString &str)

WString	toUtf16 (const string &str)

string	format (const char *fmt,...)

string	tempfile (const char *suffix CV_DEFAULT(0))

void	error (const Exception &exc)
	Signals an error and raises the exception. More...

bool	setBreakOnError (bool flag)
	Sets/resets the break-on-error mode. More...

ErrorCallback	redirectError (ErrorCallback errCallback, void userdata=0, void *prevUserdata=0)
	Sets the new error handler and the optional user data. More...

void	glob (String pattern, std::vector< String > &result, bool recursive=false)

void	setNumThreads (int nthreads)

int	getNumThreads ()

int	getThreadNum ()

const string &	getBuildInformation ()

int64	getTickCount ()
	Returns the number of ticks. More...

double	getTickFrequency ()

int64	getCPUTickCount ()

bool	checkHardwareSupport (int feature)

int	getNumberOfCPUs ()
	returns the number of CPUs (including hyper-threading) More...

void *	fastMalloc (size_t bufSize)

void	fastFree (void *ptr)

void	setUseOptimized (bool onoff)

bool	useOptimized ()

void	scalarToRawData (const Scalar &s, void *buf, int type, int unroll_to=0)

template<typename T >
Ptr< T >	makePtr ()

template<typename T , typename A1 >
Ptr< T >	makePtr (const A1 &a1)

template<typename T , typename A1 , typename A2 >
Ptr< T >	makePtr (const A1 &a1, const A2 &a2)

template<typename T , typename A1 , typename A2 , typename A3 >
Ptr< T >	makePtr (const A1 &a1, const A2 &a2, const A3 &a3)

template<typename T , typename A1 , typename A2 , typename A3 , typename A4 >
Ptr< T >	makePtr (const A1 &a1, const A2 &a2, const A3 &a3, const A4 &a4)

template<typename T , typename A1 , typename A2 , typename A3 , typename A4 , typename A5 >
Ptr< T >	makePtr (const A1 &a1, const A2 &a2, const A3 &a3, const A4 &a4, const A5 &a5)

template<typename T , typename A1 , typename A2 , typename A3 , typename A4 , typename A5 , typename A6 >
Ptr< T >	makePtr (const A1 &a1, const A2 &a2, const A3 &a3, const A4 &a4, const A5 &a5, const A6 &a6)

template<typename T , typename A1 , typename A2 , typename A3 , typename A4 , typename A5 , typename A6 , typename A7 >
Ptr< T >	makePtr (const A1 &a1, const A2 &a2, const A3 &a3, const A4 &a4, const A5 &a5, const A6 &a6, const A7 &a7)

template<typename T , typename A1 , typename A2 , typename A3 , typename A4 , typename A5 , typename A6 , typename A7 , typename A8 >
Ptr< T >	makePtr (const A1 &a1, const A2 &a2, const A3 &a3, const A4 &a4, const A5 &a5, const A6 &a6, const A7 &a7, const A8 &a8)

template<typename T , typename A1 , typename A2 , typename A3 , typename A4 , typename A5 , typename A6 , typename A7 , typename A8 , typename A9 >
Ptr< T >	makePtr (const A1 &a1, const A2 &a2, const A3 &a3, const A4 &a4, const A5 &a5, const A6 &a6, const A7 &a7, const A8 &a8, const A9 &a9)

template<typename T , typename A1 , typename A2 , typename A3 , typename A4 , typename A5 , typename A6 , typename A7 , typename A8 , typename A9 , typename A10 >
Ptr< T >	makePtr (const A1 &a1, const A2 &a2, const A3 &a3, const A4 &a4, const A5 &a5, const A6 &a6, const A7 &a7, const A8 &a8, const A9 &a9, const A10 &a10)

OutputArray	noArray ()

BinaryFunc	getConvertFunc (int sdepth, int ddepth)

BinaryFunc	getConvertScaleFunc (int sdepth, int ddepth)

BinaryFunc	getCopyMaskFunc (size_t esz)

void	swap (Mat &a, Mat &b)
	swaps two matrices More...

Mat	cvarrToMat (const CvArr *arr, bool copyData=false, bool allowND=true, int coiMode=0)
	converts array (CvMat or IplImage) to cv::Mat More...

void	extractImageCOI (const CvArr *arr, OutputArray coiimg, int coi=-1)
	extracts Channel of Interest from CvMat or IplImage and makes cv::Mat out of it. More...

void	insertImageCOI (InputArray coiimg, CvArr *arr, int coi=-1)
	inserts single-channel cv::Mat into a multi-channel CvMat or IplImage More...

void	add (InputArray src1, InputArray src2, OutputArray dst, InputArray mask=noArray(), int dtype=-1)
	adds one matrix to another (dst = src1 + src2) More...

void	subtract (InputArray src1, InputArray src2, OutputArray dst, InputArray mask=noArray(), int dtype=-1)
	subtracts one matrix from another (dst = src1 - src2) More...

void	multiply (InputArray src1, InputArray src2, OutputArray dst, double scale=1, int dtype=-1)
	computes element-wise weighted product of the two arrays (dst = scalesrc1src2) More...

void	divide (InputArray src1, InputArray src2, OutputArray dst, double scale=1, int dtype=-1)
	computes element-wise weighted quotient of the two arrays (dst = scale*src1/src2) More...

void	divide (double scale, InputArray src2, OutputArray dst, int dtype=-1)
	computes element-wise weighted reciprocal of an array (dst = scale/src2) More...

void	scaleAdd (InputArray src1, double alpha, InputArray src2, OutputArray dst)
	adds scaled array to another one (dst = alpha*src1 + src2) More...

void	addWeighted (InputArray src1, double alpha, InputArray src2, double beta, double gamma, OutputArray dst, int dtype=-1)
	computes weighted sum of two arrays (dst = alphasrc1 + betasrc2 + gamma) More...

void	convertScaleAbs (InputArray src, OutputArray dst, double alpha=1, double beta=0)
	scales array elements, computes absolute values and converts the results to 8-bit unsigned integers: dst(i)=saturate_cast<uchar>abs(src(i)*alpha+beta) More...

void	LUT (InputArray src, InputArray lut, OutputArray dst, int interpolation=0)
	transforms array of numbers using a lookup table: dst(i)=lut(src(i)) More...

	CV_EXPORTS_AS (sumElems) Scalar sum(InputArray src)
	computes sum of array elements More...

int	countNonZero (InputArray src)
	computes the number of nonzero array elements More...

void	findNonZero (InputArray src, OutputArray idx)
	returns the list of locations of non-zero pixels More...

Scalar	mean (InputArray src, InputArray mask=noArray())
	computes mean value of selected array elements More...

void	meanStdDev (InputArray src, OutputArray mean, OutputArray stddev, InputArray mask=noArray())
	computes mean value and standard deviation of all or selected array elements More...

double	norm (InputArray src1, int normType=NORM_L2, InputArray mask=noArray())
	computes norm of the selected array part More...

double	norm (InputArray src1, InputArray src2, int normType=NORM_L2, InputArray mask=noArray())
	computes norm of selected part of the difference between two arrays More...

void	batchDistance (InputArray src1, InputArray src2, OutputArray dist, int dtype, OutputArray nidx, int normType=NORM_L2, int K=0, InputArray mask=noArray(), int update=0, bool crosscheck=false)
	naive nearest neighbor finder More...

void	normalize (InputArray src, OutputArray dst, double alpha=1, double beta=0, int norm_type=NORM_L2, int dtype=-1, InputArray mask=noArray())
	scales and shifts array elements so that either the specified norm (alpha) or the minimum (alpha) and maximum (beta) array values get the specified values More...

void	minMaxLoc (InputArray src, CV_OUT double minVal, CV_OUT double maxVal=0, CV_OUT Point minLoc=0, CV_OUT Point maxLoc=0, InputArray mask=noArray())
	finds global minimum and maximum array elements and returns their values and their locations More...

void	minMaxIdx (InputArray src, double minVal, double maxVal, int minIdx=0, int maxIdx=0, InputArray mask=noArray())

void	reduce (InputArray src, OutputArray dst, int dim, int rtype, int dtype=-1)
	transforms 2D matrix to 1D row or column vector by taking sum, minimum, maximum or mean value over all the rows More...

void	merge (const Mat *mv, size_t count, OutputArray dst)
	makes multi-channel array out of several single-channel arrays More...

void	merge (const vector< Mat > &mv, OutputArray dst)

void	merge (InputArrayOfArrays mv, OutputArray dst)
	makes multi-channel array out of several single-channel arrays More...

void	split (const Mat &src, Mat *mvbegin)
	copies each plane of a multi-channel array to a dedicated array More...

void	split (const Mat &m, vector< Mat > &mv)

void	split (InputArray m, OutputArrayOfArrays mv)
	copies each plane of a multi-channel array to a dedicated array More...

void	mixChannels (const Mat src, size_t nsrcs, Mat dst, size_t ndsts, const int *fromTo, size_t npairs)
	copies selected channels from the input arrays to the selected channels of the output arrays More...

void	mixChannels (const vector< Mat > &src, vector< Mat > &dst, const int *fromTo, size_t npairs)

void	mixChannels (InputArrayOfArrays src, InputArrayOfArrays dst, const vector< int > &fromTo)

void	extractChannel (InputArray src, OutputArray dst, int coi)
	extracts a single channel from src (coi is 0-based index) More...

void	insertChannel (InputArray src, InputOutputArray dst, int coi)
	inserts a single channel to dst (coi is 0-based index) More...

void	flip (InputArray src, OutputArray dst, int flipCode)
	reverses the order of the rows, columns or both in a matrix More...

void	repeat (InputArray src, int ny, int nx, OutputArray dst)
	replicates the input matrix the specified number of times in the horizontal and/or vertical direction More...

Mat	repeat (const Mat &src, int ny, int nx)

void	hconcat (const Mat *src, size_t nsrc, OutputArray dst)

void	hconcat (InputArray src1, InputArray src2, OutputArray dst)

void	hconcat (InputArrayOfArrays src, OutputArray dst)

void	vconcat (const Mat *src, size_t nsrc, OutputArray dst)

void	vconcat (InputArray src1, InputArray src2, OutputArray dst)

void	vconcat (InputArrayOfArrays src, OutputArray dst)

void	bitwise_and (InputArray src1, InputArray src2, OutputArray dst, InputArray mask=noArray())
	computes bitwise conjunction of the two arrays (dst = src1 & src2) More...

void	bitwise_or (InputArray src1, InputArray src2, OutputArray dst, InputArray mask=noArray())
	computes bitwise disjunction of the two arrays (dst = src1 \| src2) More...

void	bitwise_xor (InputArray src1, InputArray src2, OutputArray dst, InputArray mask=noArray())
	computes bitwise exclusive-or of the two arrays (dst = src1 ^ src2) More...

void	bitwise_not (InputArray src, OutputArray dst, InputArray mask=noArray())
	inverts each bit of array (dst = ~src) More...

void	absdiff (InputArray src1, InputArray src2, OutputArray dst)
	computes element-wise absolute difference of two arrays (dst = abs(src1 - src2)) More...

void	inRange (InputArray src, InputArray lowerb, InputArray upperb, OutputArray dst)
	set mask elements for those array elements which are within the element-specific bounding box (dst = lowerb <= src && src < upperb) More...

void	compare (InputArray src1, InputArray src2, OutputArray dst, int cmpop)
	compares elements of two arrays (dst = src1 <cmpop> src2) More...

void	min (InputArray src1, InputArray src2, OutputArray dst)
	computes per-element minimum of two arrays (dst = min(src1, src2)) More...

void	max (InputArray src1, InputArray src2, OutputArray dst)
	computes per-element maximum of two arrays (dst = max(src1, src2)) More...

void	min (const Mat &src1, const Mat &src2, Mat &dst)
	computes per-element minimum of two arrays (dst = min(src1, src2)) More...

void	min (const Mat &src1, double src2, Mat &dst)
	computes per-element minimum of array and scalar (dst = min(src1, src2)) More...

void	max (const Mat &src1, const Mat &src2, Mat &dst)
	computes per-element maximum of two arrays (dst = max(src1, src2)) More...

void	max (const Mat &src1, double src2, Mat &dst)
	computes per-element maximum of array and scalar (dst = max(src1, src2)) More...

void	sqrt (InputArray src, OutputArray dst)
	computes square root of each matrix element (dst = src**0.5) More...

void	pow (InputArray src, double power, OutputArray dst)
	raises the input matrix elements to the specified power (b = a**power) More...

void	exp (InputArray src, OutputArray dst)
	computes exponent of each matrix element (dst = e**src) More...

void	log (InputArray src, OutputArray dst)
	computes natural logarithm of absolute value of each matrix element: dst = log(abs(src)) More...

float	cubeRoot (float val)
	computes cube root of the argument More...

float	fastAtan2 (float y, float x)
	computes the angle in degrees (0..360) of the vector (x,y) More...

void	exp (const float src, float dst, int n)

void	log (const float src, float dst, int n)

void	fastAtan2 (const float y, const float x, float *dst, int n, bool angleInDegrees)

void	magnitude (const float x, const float y, float *dst, int n)

void	polarToCart (InputArray magnitude, InputArray angle, OutputArray x, OutputArray y, bool angleInDegrees=false)
	converts polar coordinates to Cartesian More...

void	cartToPolar (InputArray x, InputArray y, OutputArray magnitude, OutputArray angle, bool angleInDegrees=false)
	converts Cartesian coordinates to polar More...

void	phase (InputArray x, InputArray y, OutputArray angle, bool angleInDegrees=false)
	computes angle (angle(i)) of each (x(i), y(i)) vector More...

void	magnitude (InputArray x, InputArray y, OutputArray magnitude)
	computes magnitude (magnitude(i)) of each (x(i), y(i)) vector More...

bool	checkRange (InputArray a, bool quiet=true, CV_OUT Point *pos=0, double minVal=-DBL_MAX, double maxVal=DBL_MAX)
	checks that each matrix element is within the specified range. More...

void	patchNaNs (InputOutputArray a, double val=0)
	converts NaN's to the given number More...

void	gemm (InputArray src1, InputArray src2, double alpha, InputArray src3, double beta, OutputArray dst, int flags=0)
	implements generalized matrix product algorithm GEMM from BLAS More...

void	mulTransposed (InputArray src, OutputArray dst, bool aTa, InputArray delta=noArray(), double scale=1, int dtype=-1)
	multiplies matrix by its transposition from the left or from the right More...

void	transpose (InputArray src, OutputArray dst)
	transposes the matrix More...

void	transform (InputArray src, OutputArray dst, InputArray m)
	performs affine transformation of each element of multi-channel input matrix More...

void	perspectiveTransform (InputArray src, OutputArray dst, InputArray m)
	performs perspective transformation of each element of multi-channel input matrix More...

void	completeSymm (InputOutputArray mtx, bool lowerToUpper=false)
	extends the symmetrical matrix from the lower half or from the upper half More...

void	setIdentity (InputOutputArray mtx, const Scalar &s=Scalar(1))
	initializes scaled identity matrix More...

double	determinant (InputArray mtx)
	computes determinant of a square matrix More...

Scalar	trace (InputArray mtx)
	computes trace of a matrix More...

double	invert (InputArray src, OutputArray dst, int flags=DECOMP_LU)
	computes inverse or pseudo-inverse matrix More...

bool	solve (InputArray src1, InputArray src2, OutputArray dst, int flags=DECOMP_LU)
	solves linear system or a least-square problem More...

void	sort (InputArray src, OutputArray dst, int flags)
	sorts independently each matrix row or each matrix column More...

void	sortIdx (InputArray src, OutputArray dst, int flags)
	sorts independently each matrix row or each matrix column More...

int	solveCubic (InputArray coeffs, OutputArray roots)
	finds real roots of a cubic polynomial More...

double	solvePoly (InputArray coeffs, OutputArray roots, int maxIters=300)
	finds real and complex roots of a polynomial More...

bool	eigen (InputArray src, OutputArray eigenvalues, int lowindex=-1, int highindex=-1)
	finds eigenvalues of a symmetric matrix More...

bool	eigen (InputArray src, OutputArray eigenvalues, OutputArray eigenvectors, int lowindex=-1, int highindex=-1)
	finds eigenvalues and eigenvectors of a symmetric matrix More...

bool	eigen (InputArray src, bool computeEigenvectors, OutputArray eigenvalues, OutputArray eigenvectors)

void	calcCovarMatrix (const Mat *samples, int nsamples, Mat &covar, Mat &mean, int flags, int ctype=CV_64F)
	computes covariation matrix of a set of samples More...

void	calcCovarMatrix (InputArray samples, OutputArray covar, OutputArray mean, int flags, int ctype=CV_64F)
	computes covariation matrix of a set of samples More...

void	PCACompute (InputArray data, CV_OUT InputOutputArray mean, OutputArray eigenvectors, int maxComponents=0)

void	PCAComputeVar (InputArray data, CV_OUT InputOutputArray mean, OutputArray eigenvectors, double retainedVariance)

void	PCAProject (InputArray data, InputArray mean, InputArray eigenvectors, OutputArray result)

void	PCABackProject (InputArray data, InputArray mean, InputArray eigenvectors, OutputArray result)

void	SVDecomp (InputArray src, CV_OUT OutputArray w, CV_OUT OutputArray u, CV_OUT OutputArray vt, int flags=0)
	computes SVD of src More...

void	SVBackSubst (InputArray w, InputArray u, InputArray vt, InputArray rhs, CV_OUT OutputArray dst)
	performs back substitution for the previously computed SVD More...

double	Mahalanobis (InputArray v1, InputArray v2, InputArray icovar)
	computes Mahalanobis distance between two vectors: sqrt((v1-v2)'icovar(v1-v2)), where icovar is the inverse covariation matrix More...

double	Mahalonobis (InputArray v1, InputArray v2, InputArray icovar)
	a synonym for Mahalanobis More...

void	dft (InputArray src, OutputArray dst, int flags=0, int nonzeroRows=0)
	performs forward or inverse 1D or 2D Discrete Fourier Transformation More...

void	idft (InputArray src, OutputArray dst, int flags=0, int nonzeroRows=0)
	performs inverse 1D or 2D Discrete Fourier Transformation More...

void	dct (InputArray src, OutputArray dst, int flags=0)
	performs forward or inverse 1D or 2D Discrete Cosine Transformation More...

void	idct (InputArray src, OutputArray dst, int flags=0)
	performs inverse 1D or 2D Discrete Cosine Transformation More...

void	mulSpectrums (InputArray a, InputArray b, OutputArray c, int flags, bool conjB=false)
	computes element-wise product of the two Fourier spectrums. The second spectrum can optionally be conjugated before the multiplication More...

int	getOptimalDFTSize (int vecsize)
	computes the minimal vector size vecsize1 >= vecsize so that the dft() of the vector of length vecsize1 can be computed efficiently More...

double	kmeans (InputArray data, int K, CV_OUT InputOutputArray bestLabels, TermCriteria criteria, int attempts, int flags, OutputArray centers=noArray())
	clusters the input data using k-Means algorithm More...

RNG &	theRNG ()
	returns the thread-local Random number generator More...

void	setRNGSeed (int seed)
	sets state of the thread-local Random number generator More...

void	randu (InputOutputArray dst, InputArray low, InputArray high)
	fills array with uniformly-distributed random numbers from the range [low, high) More...

void	randn (InputOutputArray dst, InputArray mean, InputArray stddev)
	fills array with normally-distributed random numbers with the specified mean and the standard deviation More...

void	randShuffle (InputOutputArray dst, double iterFactor=1., RNG *rng=0)
	shuffles the input array elements More...

	CV_EXPORTS_AS (randShuffle) void randShuffle_(InputOutputArray dst

void	line (CV_IN_OUT Mat &img, Point pt1, Point pt2, const Scalar &color, int thickness=1, int lineType=8, int shift=0)
	draws the line segment (pt1, pt2) in the image More...

void	arrowedLine (CV_IN_OUT Mat &img, Point pt1, Point pt2, const Scalar &color, int thickness=1, int line_type=8, int shift=0, double tipLength=0.1)
	draws an arrow from pt1 to pt2 in the image More...

void	rectangle (CV_IN_OUT Mat &img, Point pt1, Point pt2, const Scalar &color, int thickness=1, int lineType=8, int shift=0)
	draws the rectangle outline or a solid rectangle with the opposite corners pt1 and pt2 in the image More...

void	rectangle (CV_IN_OUT Mat &img, Rect rec, const Scalar &color, int thickness=1, int lineType=8, int shift=0)
	draws the rectangle outline or a solid rectangle covering rec in the image More...

void	circle (CV_IN_OUT Mat &img, Point center, int radius, const Scalar &color, int thickness=1, int lineType=8, int shift=0)
	draws the circle outline or a solid circle in the image More...

void	ellipse (CV_IN_OUT Mat &img, Point center, Size axes, double angle, double startAngle, double endAngle, const Scalar &color, int thickness=1, int lineType=8, int shift=0)
	draws an elliptic arc, ellipse sector or a rotated ellipse in the image More...

void	ellipse (CV_IN_OUT Mat &img, const RotatedRect &box, const Scalar &color, int thickness=1, int lineType=8)
	draws a rotated ellipse in the image More...

void	drawMarker (CV_IN_OUT Mat &img, Point position, const Scalar &color, int markerType=MARKER_CROSS, int markerSize=20, int thickness=1, int line_type=8)
	Draws a marker on a predefined position in an image. More...

void	fillConvexPoly (Mat &img, const Point *pts, int npts, const Scalar &color, int lineType=8, int shift=0)
	draws a filled convex polygon in the image More...

void	fillConvexPoly (InputOutputArray img, InputArray points, const Scalar &color, int lineType=8, int shift=0)

void	fillPoly (Mat &img, const Point *pts, const int npts, int ncontours, const Scalar &color, int lineType=8, int shift=0, Point offset=Point())
	fills an area bounded by one or more polygons More...

void	fillPoly (InputOutputArray img, InputArrayOfArrays pts, const Scalar &color, int lineType=8, int shift=0, Point offset=Point())

void	polylines (Mat &img, const Point *pts, const int npts, int ncontours, bool isClosed, const Scalar &color, int thickness=1, int lineType=8, int shift=0)
	draws one or more polygonal curves More...

void	polylines (InputOutputArray img, InputArrayOfArrays pts, bool isClosed, const Scalar &color, int thickness=1, int lineType=8, int shift=0)

bool	clipLine (Size imgSize, CV_IN_OUT Point &pt1, CV_IN_OUT Point &pt2)
	clips the line segment by the rectangle Rect(0, 0, imgSize.width, imgSize.height) More...

bool	clipLine (Size2l imgSize, CV_IN_OUT Point2l &pt1, CV_IN_OUT Point2l &pt2)

bool	clipLine (Rect imgRect, CV_OUT CV_IN_OUT Point &pt1, CV_OUT CV_IN_OUT Point &pt2)
	clips the line segment by the rectangle imgRect More...

void	ellipse2Poly (Point center, Size axes, int angle, int arcStart, int arcEnd, int delta, CV_OUT vector< Point > &pts)
	converts elliptic arc to a polygonal curve More...

void	ellipse2Poly (Point2d center, Size2d axes, int angle, int arcStart, int arcEnd, int delta, CV_OUT vector< Point2d > &pts)

void	putText (Mat &img, const string &text, Point org, int fontFace, double fontScale, Scalar color, int thickness=1, int lineType=8, bool bottomLeftOrigin=false)
	renders text string in the image More...

Size	getTextSize (const string &text, int fontFace, double fontScale, int thickness, CV_OUT int *baseLine)
	returns bounding box of the text string More...

ConvertData	getConvertElem (int fromType, int toType)
	returns the function for converting pixels from one data type to another More...

ConvertScaleData	getConvertScaleElem (int fromType, int toType)
	returns the function for converting pixels from one data type to another with the optional scaling More...

void	minMaxLoc (const SparseMat &a, double minVal, double maxVal, int minIdx=0, int maxIdx=0)
	finds global minimum and maximum sparse array elements and returns their values and their locations More...

double	norm (const SparseMat &src, int normType)
	computes norm of a sparse matrix More...

void	normalize (const SparseMat &src, SparseMat &dst, double alpha, int normType)
	scales and shifts array elements so that either the specified norm (alpha) or the minimum (alpha) and maximum (beta) array values get the specified values More...

template<>
std::string	CommandLineParser::analyzeValue< std::string > (const std::string &str, bool space_delete)

void	parallel_for_ (const Range &range, const ParallelLoopBody &body, double nstripes=-1.)

template<>
uchar	saturate_cast< uchar > (schar v)

template<>
uchar	saturate_cast< uchar > (ushort v)

template<>
uchar	saturate_cast< uchar > (int v)

template<>
uchar	saturate_cast< uchar > (short v)

template<>
uchar	saturate_cast< uchar > (unsigned v)

template<>
uchar	saturate_cast< uchar > (float v)

template<>
uchar	saturate_cast< uchar > (double v)

template<>
schar	saturate_cast< schar > (uchar v)

template<>
schar	saturate_cast< schar > (ushort v)

template<>
schar	saturate_cast< schar > (int v)

template<>
schar	saturate_cast< schar > (short v)

template<>
schar	saturate_cast< schar > (unsigned v)

template<>
schar	saturate_cast< schar > (float v)

template<>
schar	saturate_cast< schar > (double v)

template<>
ushort	saturate_cast< ushort > (schar v)

template<>
ushort	saturate_cast< ushort > (short v)

template<>
ushort	saturate_cast< ushort > (int v)

template<>
ushort	saturate_cast< ushort > (unsigned v)

template<>
ushort	saturate_cast< ushort > (float v)

template<>
ushort	saturate_cast< ushort > (double v)

template<>
short	saturate_cast< short > (ushort v)

template<>
short	saturate_cast< short > (int v)

template<>
short	saturate_cast< short > (unsigned v)

template<>
short	saturate_cast< short > (float v)

template<>
short	saturate_cast< short > (double v)

template<>
int	saturate_cast< int > (float v)

template<>
int	saturate_cast< int > (double v)

template<>
unsigned	saturate_cast< unsigned > (float v)

template<>
unsigned	saturate_cast< unsigned > (double v)

int	fast_abs (uchar v)

int	fast_abs (schar v)

int	fast_abs (ushort v)

int	fast_abs (short v)

int	fast_abs (int v)

float	fast_abs (float v)

double	fast_abs (double v)

int	LU (float A, size_t astep, int m, float b, size_t bstep, int n)

int	LU (double A, size_t astep, int m, double b, size_t bstep, int n)

bool	Cholesky (float A, size_t astep, int m, float b, size_t bstep, int n)

bool	Cholesky (double A, size_t astep, int m, double b, size_t bstep, int n)

float	normL2Sqr_ (const float a, const float b, int n)

float	normL1_ (const float a, const float b, int n)

int	normL1_ (const uchar a, const uchar b, int n)

int	normHamming (const uchar a, const uchar b, int n)

int	normHamming (const uchar a, const uchar b, int n, int cellSize)

template<>
float	normL2Sqr (const float a, const float b, int n)

template<>
float	normL1 (const float a, const float b, int n)

template<>
int	normL1 (const uchar a, const uchar b, int n)

template<typename _Tp >
Vec< _Tp, 2 >	conjugate (const Vec< _Tp, 2 > &v)

template<typename _Tp >
Vec< _Tp, 4 >	conjugate (const Vec< _Tp, 4 > &v)

template<typename _Tp >
Vec< _Tp, 4 >	operator* (const Vec< _Tp, 4 > &v1, const Vec< _Tp, 4 > &v2)

template<typename _Tp >
Vec< _Tp, 4 > &	operator*= (Vec< _Tp, 4 > &v1, const Vec< _Tp, 4 > &v2)

template<typename _Tp , int cn>
Vec< _Tp, cn >	normalize (const Vec< _Tp, cn > &v)

template<typename _Tp >
DataType< _Tp >::work_type	dot (const Vector< _Tp > &v1, const Vector< _Tp > &v2)

void	write (FileStorage &fs, const string &name, int value)

void	write (FileStorage &fs, const string &name, float value)

void	write (FileStorage &fs, const string &name, double value)

void	write (FileStorage &fs, const string &name, const string &value)

template<typename _Tp >
void	write (FileStorage &fs, const _Tp &value)

void	writeScalar (FileStorage &fs, int value)

void	writeScalar (FileStorage &fs, float value)

void	writeScalar (FileStorage &fs, double value)

void	writeScalar (FileStorage &fs, const string &value)

template<>
void	write (FileStorage &fs, const int &value)

template<>
void	write (FileStorage &fs, const float &value)

template<>
void	write (FileStorage &fs, const double &value)

template<>
void	write (FileStorage &fs, const string &value)

template<typename _Tp >
void	write (FileStorage &fs, const Point_< _Tp > &pt)

template<typename _Tp >
void	write (FileStorage &fs, const Point3_< _Tp > &pt)

template<typename _Tp >
void	write (FileStorage &fs, const Size_< _Tp > &sz)

template<typename _Tp >
void	write (FileStorage &fs, const Complex< _Tp > &c)

template<typename _Tp >
void	write (FileStorage &fs, const Rect_< _Tp > &r)

template<typename _Tp , int cn>
void	write (FileStorage &fs, const Vec< _Tp, cn > &v)

template<typename _Tp >
void	write (FileStorage &fs, const Scalar_< _Tp > &s)

void	write (FileStorage &fs, const Range &r)

template<typename _Tp >
void	write (FileStorage &fs, const string &name, const Point_< _Tp > &pt)

template<typename _Tp >
void	write (FileStorage &fs, const string &name, const Point3_< _Tp > &pt)

template<typename _Tp >
void	write (FileStorage &fs, const string &name, const Size_< _Tp > &sz)

template<typename _Tp >
void	write (FileStorage &fs, const string &name, const Complex< _Tp > &c)

template<typename _Tp >
void	write (FileStorage &fs, const string &name, const Rect_< _Tp > &r)

template<typename _Tp , int cn>
void	write (FileStorage &fs, const string &name, const Vec< _Tp, cn > &v)

template<typename _Tp >
void	write (FileStorage &fs, const string &name, const Scalar_< _Tp > &s)

void	write (FileStorage &fs, const string &name, const Range &r)

void	write (FileStorage &fs, const string &name, const Mat &value)

void	write (FileStorage &fs, const string &name, const SparseMat &value)

FileStorage &	operator<< (FileStorage &fs, const string &str)

void	read (const FileNode &node, Mat &mat, const Mat &default_mat=Mat())

void	read (const FileNode &node, SparseMat &mat, const SparseMat &default_mat=SparseMat())

template<typename _Tp , class _LT >
void	sort (vector< _Tp > &vec, _LT LT=_LT())

template<typename _Tp , class _EqPredicate >
int	partition (const vector< _Tp > &_vec, vector< int > &labels, _EqPredicate predicate=_EqPredicate())

schar *	seqPush (CvSeq seq, const void element=0)

schar *	seqPushFront (CvSeq seq, const void element=0)

void	seqPop (CvSeq seq, void element=0)

void	seqPopFront (CvSeq seq, void element=0)

void	seqPopMulti (CvSeq seq, void elements, int count, int in_front=0)

void	seqRemove (CvSeq *seq, int index)

void	clearSeq (CvSeq *seq)

schar *	getSeqElem (const CvSeq *seq, int index)

void	seqRemoveSlice (CvSeq *seq, CvSlice slice)

void	seqInsertSlice (CvSeq seq, int before_index, const CvArr from_arr)

template<typename _Tp >
ptrdiff_t	operator- (const SeqIterator< _Tp > &a, const SeqIterator< _Tp > &b)

template<typename _Tp >
bool	operator== (const SeqIterator< _Tp > &a, const SeqIterator< _Tp > &b)

template<typename _Tp >
bool	operator!= (const SeqIterator< _Tp > &a, const SeqIterator< _Tp > &b)

template<typename _Tp , int m, int n>
std::ostream &	operator<< (std::ostream &out, const Matx< _Tp, m, n > &matx)

template<typename _Tp >
std::ostream &	operator<< (std::ostream &out, const Point_< _Tp > &p)

template<typename _Tp >
std::ostream &	operator<< (std::ostream &out, const Point3_< _Tp > &p)

template<typename _Tp , int n>
std::ostream &	operator<< (std::ostream &out, const Vec< _Tp, n > &vec)

template<typename _Tp >
std::ostream &	operator<< (std::ostream &out, const Size_< _Tp > &size)

template<typename _Tp >
std::ostream &	operator<< (std::ostream &out, const Rect_< _Tp > &rect)

int	borderInterpolate (int p, int len, int borderType)
	1D interpolation function: returns coordinate of the "donor" pixel for the specified location p. More...

int	getKernelType (InputArray kernel, Point anchor)
	returns type (one of KERNEL_*) of 1D or 2D kernel specified by its coefficients. More...

Ptr< BaseRowFilter >	getLinearRowFilter (int srcType, int bufType, InputArray kernel, int anchor, int symmetryType)
	returns the primitive row filter with the specified kernel More...

Ptr< BaseColumnFilter >	getLinearColumnFilter (int bufType, int dstType, InputArray kernel, int anchor, int symmetryType, double delta=0, int bits=0)
	returns the primitive column filter with the specified kernel More...

Ptr< BaseFilter >	getLinearFilter (int srcType, int dstType, InputArray kernel, Point anchor=Point(-1,-1), double delta=0, int bits=0)
	returns 2D filter with the specified kernel More...

Ptr< FilterEngine >	createSeparableLinearFilter (int srcType, int dstType, InputArray rowKernel, InputArray columnKernel, Point anchor=Point(-1,-1), double delta=0, int rowBorderType=BORDER_DEFAULT, int columnBorderType=-1, const Scalar &borderValue=Scalar())
	returns the separable linear filter engine More...

Ptr< FilterEngine >	createLinearFilter (int srcType, int dstType, InputArray kernel, Point _anchor=Point(-1,-1), double delta=0, int rowBorderType=BORDER_DEFAULT, int columnBorderType=-1, const Scalar &borderValue=Scalar())
	returns the non-separable linear filter engine More...

Mat	getGaussianKernel (int ksize, double sigma, int ktype=CV_64F)
	returns the Gaussian kernel with the specified parameters More...

Ptr< FilterEngine >	createGaussianFilter (int type, Size ksize, double sigma1, double sigma2=0, int borderType=BORDER_DEFAULT)
	returns the Gaussian filter engine More...

void	getDerivKernels (OutputArray kx, OutputArray ky, int dx, int dy, int ksize, bool normalize=false, int ktype=CV_32F)
	initializes kernels of the generalized Sobel operator More...

Ptr< FilterEngine >	createDerivFilter (int srcType, int dstType, int dx, int dy, int ksize, int borderType=BORDER_DEFAULT)
	returns filter engine for the generalized Sobel operator More...

Ptr< BaseRowFilter >	getRowSumFilter (int srcType, int sumType, int ksize, int anchor=-1)
	returns horizontal 1D box filter More...

Ptr< BaseColumnFilter >	getColumnSumFilter (int sumType, int dstType, int ksize, int anchor=-1, double scale=1)
	returns vertical 1D box filter More...

Ptr< FilterEngine >	createBoxFilter (int srcType, int dstType, Size ksize, Point anchor=Point(-1,-1), bool normalize=true, int borderType=BORDER_DEFAULT)
	returns box filter engine More...

Mat	getGaborKernel (Size ksize, double sigma, double theta, double lambd, double gamma, double psi=CV_PI *0.5, int ktype=CV_64F)
	returns the Gabor kernel with the specified parameters More...

Ptr< BaseRowFilter >	getMorphologyRowFilter (int op, int type, int ksize, int anchor=-1)
	returns horizontal 1D morphological filter More...

Ptr< BaseColumnFilter >	getMorphologyColumnFilter (int op, int type, int ksize, int anchor=-1)
	returns vertical 1D morphological filter More...

Ptr< BaseFilter >	getMorphologyFilter (int op, int type, InputArray kernel, Point anchor=Point(-1,-1))
	returns 2D morphological filter More...

Ptr< FilterEngine >	createMorphologyFilter (int op, int type, InputArray kernel, Point anchor=Point(-1,-1), int rowBorderType=BORDER_CONSTANT, int columnBorderType=-1, const Scalar &borderValue=morphologyDefaultBorderValue())
	returns morphological filter engine. Only MORPH_ERODE and MORPH_DILATE are supported. More...

Mat	getStructuringElement (int shape, Size ksize, Point anchor=Point(-1,-1))
	returns structuring element of the specified shape and size More...

void	copyMakeBorder (InputArray src, OutputArray dst, int top, int bottom, int left, int right, int borderType, const Scalar &value=Scalar())
	copies 2D array to a larger destination array with extrapolation of the outer part of src using the specified border mode More...

void	medianBlur (InputArray src, OutputArray dst, int ksize)
	smooths the image using median filter. More...

void	GaussianBlur (InputArray src, OutputArray dst, Size ksize, double sigmaX, double sigmaY=0, int borderType=BORDER_DEFAULT)
	smooths the image using Gaussian filter. More...

void	bilateralFilter (InputArray src, OutputArray dst, int d, double sigmaColor, double sigmaSpace, int borderType=BORDER_DEFAULT)
	smooths the image using bilateral filter More...

void	adaptiveBilateralFilter (InputArray src, OutputArray dst, Size ksize, double sigmaSpace, double maxSigmaColor=20.0, Point anchor=Point(-1, -1), int borderType=BORDER_DEFAULT)
	smooths the image using adaptive bilateral filter More...

void	boxFilter (InputArray src, OutputArray dst, int ddepth, Size ksize, Point anchor=Point(-1,-1), bool normalize=true, int borderType=BORDER_DEFAULT)
	smooths the image using the box filter. Each pixel is processed in O(1) time More...

void	blur (InputArray src, OutputArray dst, Size ksize, Point anchor=Point(-1,-1), int borderType=BORDER_DEFAULT)
	a synonym for normalized box filter More...

void	filter2D (InputArray src, OutputArray dst, int ddepth, InputArray kernel, Point anchor=Point(-1,-1), double delta=0, int borderType=BORDER_DEFAULT)
	applies non-separable 2D linear filter to the image More...

void	sepFilter2D (InputArray src, OutputArray dst, int ddepth, InputArray kernelX, InputArray kernelY, Point anchor=Point(-1,-1), double delta=0, int borderType=BORDER_DEFAULT)
	applies separable 2D linear filter to the image More...

void	Sobel (InputArray src, OutputArray dst, int ddepth, int dx, int dy, int ksize=3, double scale=1, double delta=0, int borderType=BORDER_DEFAULT)
	applies generalized Sobel operator to the image More...

void	Scharr (InputArray src, OutputArray dst, int ddepth, int dx, int dy, double scale=1, double delta=0, int borderType=BORDER_DEFAULT)
	applies the vertical or horizontal Scharr operator to the image More...

void	Laplacian (InputArray src, OutputArray dst, int ddepth, int ksize=1, double scale=1, double delta=0, int borderType=BORDER_DEFAULT)
	applies Laplacian operator to the image More...

void	Canny (InputArray image, OutputArray edges, double threshold1, double threshold2, int apertureSize=3, bool L2gradient=false)
	applies Canny edge detector and produces the edge map. More...

void	cornerMinEigenVal (InputArray src, OutputArray dst, int blockSize, int ksize=3, int borderType=BORDER_DEFAULT)
	computes minimum eigen value of 2x2 derivative covariation matrix at each pixel - the cornerness criteria More...

void	cornerHarris (InputArray src, OutputArray dst, int blockSize, int ksize, double k, int borderType=BORDER_DEFAULT)
	computes Harris cornerness criteria at each image pixel More...

void	eigen2x2 (const float a, float e, int n)

void	cornerEigenValsAndVecs (InputArray src, OutputArray dst, int blockSize, int ksize, int borderType=BORDER_DEFAULT)
	computes both eigenvalues and the eigenvectors of 2x2 derivative covariation matrix at each pixel. The output is stored as 6-channel matrix. More...

void	preCornerDetect (InputArray src, OutputArray dst, int ksize, int borderType=BORDER_DEFAULT)
	computes another complex cornerness criteria at each pixel More...

void	cornerSubPix (InputArray image, InputOutputArray corners, Size winSize, Size zeroZone, TermCriteria criteria)
	adjusts the corner locations with sub-pixel accuracy to maximize the certain cornerness criteria More...

void	goodFeaturesToTrack (InputArray image, OutputArray corners, int maxCorners, double qualityLevel, double minDistance, InputArray mask=noArray(), int blockSize=3, bool useHarrisDetector=false, double k=0.04)
	finds the strong enough corners where the cornerMinEigenVal() or cornerHarris() report the local maxima More...

void	HoughLines (InputArray image, OutputArray lines, double rho, double theta, int threshold, double srn=0, double stn=0)
	finds lines in the black-n-white image using the standard or pyramid Hough transform More...

void	HoughLinesP (InputArray image, OutputArray lines, double rho, double theta, int threshold, double minLineLength=0, double maxLineGap=0)
	finds line segments in the black-n-white image using probabilistic Hough transform More...

void	HoughCircles (InputArray image, OutputArray circles, int method, double dp, double minDist, double param1=100, double param2=100, int minRadius=0, int maxRadius=0)
	finds circles in the grayscale image using 2+1 gradient Hough transform More...

void	erode (InputArray src, OutputArray dst, InputArray kernel, Point anchor=Point(-1,-1), int iterations=1, int borderType=BORDER_CONSTANT, const Scalar &borderValue=morphologyDefaultBorderValue())
	erodes the image (applies the local minimum operator) More...

void	dilate (InputArray src, OutputArray dst, InputArray kernel, Point anchor=Point(-1,-1), int iterations=1, int borderType=BORDER_CONSTANT, const Scalar &borderValue=morphologyDefaultBorderValue())
	dilates the image (applies the local maximum operator) More...

void	morphologyEx (InputArray src, OutputArray dst, int op, InputArray kernel, Point anchor=Point(-1,-1), int iterations=1, int borderType=BORDER_CONSTANT, const Scalar &borderValue=morphologyDefaultBorderValue())
	applies an advanced morphological operation to the image More...

void	resize (InputArray src, OutputArray dst, Size dsize, double fx=0, double fy=0, int interpolation=INTER_LINEAR)
	resizes the image More...

void	warpAffine (InputArray src, OutputArray dst, InputArray M, Size dsize, int flags=INTER_LINEAR, int borderMode=BORDER_CONSTANT, const Scalar &borderValue=Scalar())
	warps the image using affine transformation More...

void	warpPerspective (InputArray src, OutputArray dst, InputArray M, Size dsize, int flags=INTER_LINEAR, int borderMode=BORDER_CONSTANT, const Scalar &borderValue=Scalar())
	warps the image using perspective transformation More...

void	remap (InputArray src, OutputArray dst, InputArray map1, InputArray map2, int interpolation, int borderMode=BORDER_CONSTANT, const Scalar &borderValue=Scalar())
	warps the image using the precomputed maps. The maps are stored in either floating-point or integer fixed-point format More...

void	convertMaps (InputArray map1, InputArray map2, OutputArray dstmap1, OutputArray dstmap2, int dstmap1type, bool nninterpolation=false)
	converts maps for remap from floating-point to fixed-point format or backwards More...

Mat	getRotationMatrix2D (Point2f center, double angle, double scale)
	returns 2x3 affine transformation matrix for the planar rotation. More...

Mat	getPerspectiveTransform (const Point2f src[], const Point2f dst[])
	returns 3x3 perspective transformation for the corresponding 4 point pairs. More...

Mat	getAffineTransform (const Point2f src[], const Point2f dst[])
	returns 2x3 affine transformation for the corresponding 3 point pairs. More...

void	invertAffineTransform (InputArray M, OutputArray iM)
	computes 2x3 affine transformation matrix that is inverse to the specified 2x3 affine transformation. More...

Mat	getPerspectiveTransform (InputArray src, InputArray dst)

Mat	getAffineTransform (InputArray src, InputArray dst)

void	getRectSubPix (InputArray image, Size patchSize, Point2f center, OutputArray patch, int patchType=-1)
	extracts rectangle from the image at sub-pixel location More...

void	integral (InputArray src, OutputArray sum, int sdepth=-1)
	computes the integral image More...

	CV_EXPORTS_AS (integral2) void integral(InputArray src
	computes the integral image and integral for the squared image More...

	CV_EXPORTS_AS (integral3) void integral(InputArray src
	computes the integral image, integral for the squared image and the tilted integral image More...

void	accumulate (InputArray src, InputOutputArray dst, InputArray mask=noArray())
	adds image to the accumulator (dst += src). Unlike cv::add, dst and src can have different types. More...

void	accumulateSquare (InputArray src, InputOutputArray dst, InputArray mask=noArray())
	adds squared src image to the accumulator (dst += src*src). More...

void	accumulateProduct (InputArray src1, InputArray src2, InputOutputArray dst, InputArray mask=noArray())
	adds product of the 2 images to the accumulator (dst += src1*src2). More...

void	accumulateWeighted (InputArray src, InputOutputArray dst, double alpha, InputArray mask=noArray())
	updates the running average (dst = dst(1-alpha) + srcalpha) More...

double	PSNR (InputArray src1, InputArray src2)
	computes PSNR image/video quality metric More...

Point2d	phaseCorrelate (InputArray src1, InputArray src2, InputArray window=noArray())

Point2d	phaseCorrelateRes (InputArray src1, InputArray src2, InputArray window, CV_OUT double *response=0)

void	createHanningWindow (OutputArray dst, Size winSize, int type)

double	threshold (InputArray src, OutputArray dst, double thresh, double maxval, int type)
	applies fixed threshold to the image More...

void	adaptiveThreshold (InputArray src, OutputArray dst, double maxValue, int adaptiveMethod, int thresholdType, int blockSize, double C)
	applies variable (adaptive) threshold to the image More...

void	pyrDown (InputArray src, OutputArray dst, const Size &dstsize=Size(), int borderType=BORDER_DEFAULT)
	smooths and downsamples the image More...

void	pyrUp (InputArray src, OutputArray dst, const Size &dstsize=Size(), int borderType=BORDER_DEFAULT)
	upsamples and smoothes the image More...

void	buildPyramid (InputArray src, OutputArrayOfArrays dst, int maxlevel, int borderType=BORDER_DEFAULT)
	builds the gaussian pyramid using pyrDown() as a basic operation More...

void	undistort (InputArray src, OutputArray dst, InputArray cameraMatrix, InputArray distCoeffs, InputArray newCameraMatrix=noArray())
	corrects lens distortion for the given camera matrix and distortion coefficients More...

void	initUndistortRectifyMap (InputArray cameraMatrix, InputArray distCoeffs, InputArray R, InputArray newCameraMatrix, Size size, int m1type, OutputArray map1, OutputArray map2)
	initializes maps for cv::remap() to correct lens distortion and optionally rectify the image More...

float	initWideAngleProjMap (InputArray cameraMatrix, InputArray distCoeffs, Size imageSize, int destImageWidth, int m1type, OutputArray map1, OutputArray map2, int projType=PROJ_SPHERICAL_EQRECT, double alpha=0)
	initializes maps for cv::remap() for wide-angle More...

Mat	getDefaultNewCameraMatrix (InputArray cameraMatrix, Size imgsize=Size(), bool centerPrincipalPoint=false)
	returns the default new camera matrix (by default it is the same as cameraMatrix unless centerPricipalPoint=true) More...

void	undistortPoints (InputArray src, OutputArray dst, InputArray cameraMatrix, InputArray distCoeffs, InputArray R=noArray(), InputArray P=noArray())
	returns points' coordinates after lens distortion correction More...

void	calcHist (const Mat images, int nimages, const int channels, InputArray mask, OutputArray hist, int dims, const int histSize, const float *ranges, bool uniform=true, bool accumulate=false)
	computes the joint dense histogram for a set of images. More...

void	calcHist (const Mat images, int nimages, const int channels, InputArray mask, SparseMat &hist, int dims, const int histSize, const float *ranges, bool uniform=true, bool accumulate=false)
	computes the joint sparse histogram for a set of images. More...

void	calcHist (InputArrayOfArrays images, const vector< int > &channels, InputArray mask, OutputArray hist, const vector< int > &histSize, const vector< float > &ranges, bool accumulate=false)

void	calcBackProject (const Mat images, int nimages, const int channels, InputArray hist, OutputArray backProject, const float **ranges, double scale=1, bool uniform=true)
	computes back projection for the set of images More...

void	calcBackProject (const Mat images, int nimages, const int channels, const SparseMat &hist, OutputArray backProject, const float **ranges, double scale=1, bool uniform=true)
	computes back projection for the set of images More...

void	calcBackProject (InputArrayOfArrays images, const vector< int > &channels, InputArray hist, OutputArray dst, const vector< float > &ranges, double scale)

double	compareHist (InputArray H1, InputArray H2, int method)
	compares two histograms stored in dense arrays More...

double	compareHist (const SparseMat &H1, const SparseMat &H2, int method)
	compares two histograms stored in sparse arrays More...

void	equalizeHist (InputArray src, OutputArray dst)
	normalizes the grayscale image brightness and contrast by normalizing its histogram More...

Ptr< CLAHE >	createCLAHE (double clipLimit=40.0, Size tileGridSize=Size(8, 8))

float	EMD (InputArray signature1, InputArray signature2, int distType, InputArray cost=noArray(), float *lowerBound=0, OutputArray flow=noArray())

void	watershed (InputArray image, InputOutputArray markers)
	segments the image using watershed algorithm More...

void	pyrMeanShiftFiltering (InputArray src, OutputArray dst, double sp, double sr, int maxLevel=1, TermCriteria termcrit=TermCriteria(TermCriteria::MAX_ITER+TermCriteria::EPS, 5, 1))
	filters image using meanshift algorithm More...

void	grabCut (InputArray img, InputOutputArray mask, Rect rect, InputOutputArray bgdModel, InputOutputArray fgdModel, int iterCount, int mode=GC_EVAL)
	segments the image using GrabCut algorithm More...

	CV_EXPORTS_AS (distanceTransformWithLabels) void distanceTransform(InputArray src
	builds the discrete Voronoi diagram More...

void	distanceTransform (InputArray src, OutputArray dst, int distanceType, int maskSize)
	computes the distance transform map More...

int	floodFill (InputOutputArray image, Point seedPoint, Scalar newVal, CV_OUT Rect *rect=0, Scalar loDiff=Scalar(), Scalar upDiff=Scalar(), int flags=4)
	fills the semi-uniform image region starting from the specified seed point More...

int	floodFill (InputOutputArray image, InputOutputArray mask, Point seedPoint, Scalar newVal, CV_OUT Rect *rect=0, Scalar loDiff=Scalar(), Scalar upDiff=Scalar(), int flags=4)
	fills the semi-uniform image region and/or the mask starting from the specified seed point More...

void	cvtColor (InputArray src, OutputArray dst, int code, int dstCn=0)
	converts image from one color space to another More...

Moments	moments (InputArray array, bool binaryImage=false)
	computes moments of the rasterized shape or a vector of points More...

void	HuMoments (const Moments &moments, double hu[7])
	computes 7 Hu invariants from the moments More...

void	HuMoments (const Moments &m, CV_OUT OutputArray hu)

void	matchTemplate (InputArray image, InputArray templ, OutputArray result, int method)
	computes the proximity map for the raster template and the image where the template is searched for More...

void	findContours (InputOutputArray image, OutputArrayOfArrays contours, OutputArray hierarchy, int mode, int method, Point offset=Point())
	retrieves contours and the hierarchical information from black-n-white image. More...

void	findContours (InputOutputArray image, OutputArrayOfArrays contours, int mode, int method, Point offset=Point())
	retrieves contours from black-n-white image. More...

void	drawContours (InputOutputArray image, InputArrayOfArrays contours, int contourIdx, const Scalar &color, int thickness=1, int lineType=8, InputArray hierarchy=noArray(), int maxLevel=INT_MAX, Point offset=Point())
	draws contours in the image More...

void	approxPolyDP (InputArray curve, OutputArray approxCurve, double epsilon, bool closed)
	approximates contour or a curve using Douglas-Peucker algorithm More...

double	arcLength (InputArray curve, bool closed)
	computes the contour perimeter (closed=true) or a curve length More...

Rect	boundingRect (InputArray points)
	computes the bounding rectangle for a contour More...

double	contourArea (InputArray contour, bool oriented=false)
	computes the contour area More...

RotatedRect	minAreaRect (InputArray points)
	computes the minimal rotated rectangle for a set of points More...

void	minEnclosingCircle (InputArray points, CV_OUT Point2f &center, CV_OUT float &radius)
	computes the minimal enclosing circle for a set of points More...

double	matchShapes (InputArray contour1, InputArray contour2, int method, double parameter)
	matches two contours using one of the available algorithms More...

void	convexHull (InputArray points, OutputArray hull, bool clockwise=false, bool returnPoints=true)
	computes convex hull for a set of 2D points. More...

void	convexityDefects (InputArray contour, InputArray convexhull, OutputArray convexityDefects)
	computes the contour convexity defects More...

bool	isContourConvex (InputArray contour)
	returns true if the contour is convex. Does not support contours with self-intersection More...

float	intersectConvexConvex (InputArray _p1, InputArray _p2, OutputArray _p12, bool handleNested=true)
	finds intersection of two convex polygons More...

RotatedRect	fitEllipse (InputArray points)
	fits ellipse to the set of 2D points More...

void	fitLine (InputArray points, OutputArray line, int distType, double param, double reps, double aeps)
	fits line to the set of 2D points using M-estimator algorithm More...

double	pointPolygonTest (InputArray contour, Point2f pt, bool measureDist)
	checks if the point is inside the contour. Optionally computes the signed distance from the point to the contour boundary More...

void	namedWindow (const string &winname, int flags=WINDOW_AUTOSIZE)

void	destroyWindow (const string &winname)

void	destroyAllWindows ()

int	startWindowThread ()

int	waitKey (int delay=0)

void	imshow (const string &winname, InputArray mat)

void	resizeWindow (const string &winname, int width, int height)

void	moveWindow (const string &winname, int x, int y)

void	setWindowProperty (const string &winname, int prop_id, double prop_value)

double	getWindowProperty (const string &winname, int prop_id)

void	setMouseCallback (const string &winname, MouseCallback onMouse, void *userdata=0)
	assigns callback for mouse events More...

int	createTrackbar (const string &trackbarname, const string &winname, int value, int count, TrackbarCallback onChange=0, void userdata=0)

int	getTrackbarPos (const string &trackbarname, const string &winname)

void	setTrackbarPos (const string &trackbarname, const string &winname, int pos)

void	setOpenGlDrawCallback (const string &winname, OpenGlDrawCallback onOpenGlDraw, void *userdata=0)

void	setOpenGlContext (const string &winname)

void	updateWindow (const string &winname)

void	pointCloudShow (const string &winname, const GlCamera &camera, const GlArrays &arr)

void	pointCloudShow (const string &winname, const GlCamera &camera, InputArray points, InputArray colors=noArray())

CvFont	fontQt (const string &nameFont, int pointSize=-1, Scalar color=Scalar::all(0), int weight=CV_FONT_NORMAL, int style=CV_STYLE_NORMAL, int spacing=0)

void	addText (const Mat &img, const string &text, Point org, CvFont font)

void	displayOverlay (const string &winname, const string &text, int delayms CV_DEFAULT(0))

void	displayStatusBar (const string &winname, const string &text, int delayms CV_DEFAULT(0))

void	saveWindowParameters (const string &windowName)

void	loadWindowParameters (const string &windowName)

int	startLoop (int(pt2Func)(int argc, char argv[]), int argc, char *argv[])

void	stopLoop ()

int	createButton (const string &bar_name, ButtonCallback on_change, void *userdata=NULL, int type=CV_PUSH_BUTTON, bool initial_button_state=0)

Mat	imread (const string &filename, int flags=1)

bool	imwrite (const string &filename, InputArray img, const vector< int > &params=vector< int >())

Mat	imdecode (InputArray buf, int flags)

Mat	imdecode (InputArray buf, int flags, Mat *dst)

bool	imencode (const string &ext, InputArray img, CV_OUT vector< uchar > &buf, const vector< int > &params=vector< int >())

bool	initModule_video (void)

void	updateMotionHistory (InputArray silhouette, InputOutputArray mhi, double timestamp, double duration)
	updates motion history image using the current silhouette More...

void	calcMotionGradient (InputArray mhi, OutputArray mask, OutputArray orientation, double delta1, double delta2, int apertureSize=3)
	computes the motion gradient orientation image from the motion history image More...

double	calcGlobalOrientation (InputArray orientation, InputArray mask, InputArray mhi, double timestamp, double duration)
	computes the global orientation of the selected motion history image part More...

void	segmentMotion (InputArray mhi, OutputArray segmask, CV_OUT vector< Rect > &boundingRects, double timestamp, double segThresh)

RotatedRect	CamShift (InputArray probImage, CV_OUT CV_IN_OUT Rect &window, TermCriteria criteria)
	updates the object tracking window using CAMSHIFT algorithm More...

int	meanShift (InputArray probImage, CV_OUT CV_IN_OUT Rect &window, TermCriteria criteria)
	updates the object tracking window using meanshift algorithm More...

int	buildOpticalFlowPyramid (InputArray img, OutputArrayOfArrays pyramid, Size winSize, int maxLevel, bool withDerivatives=true, int pyrBorder=BORDER_REFLECT_101, int derivBorder=BORDER_CONSTANT, bool tryReuseInputImage=true)
	constructs a pyramid which can be used as input for calcOpticalFlowPyrLK More...

void	calcOpticalFlowPyrLK (InputArray prevImg, InputArray nextImg, InputArray prevPts, CV_OUT InputOutputArray nextPts, OutputArray status, OutputArray err, Size winSize=Size(21, 21), int maxLevel=3, TermCriteria criteria=TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, 30, 0.01), int flags=0, double minEigThreshold=1e-4)
	computes sparse optical flow using multi-scale Lucas-Kanade algorithm More...

void	calcOpticalFlowFarneback (InputArray prev, InputArray next, CV_OUT InputOutputArray flow, double pyr_scale, int levels, int winsize, int iterations, int poly_n, double poly_sigma, int flags)
	computes dense optical flow using Farneback algorithm More...

Mat	estimateRigidTransform (InputArray src, InputArray dst, bool fullAffine)
	estimates the best-fit Euqcidean, similarity, affine or perspective transformation More...

void	calcOpticalFlowSF (Mat &from, Mat &to, Mat &flow, int layers, int averaging_block_size, int max_flow)
	computes dense optical flow using Simple Flow algorithm More...

void	calcOpticalFlowSF (Mat &from, Mat &to, Mat &flow, int layers, int averaging_block_size, int max_flow, double sigma_dist, double sigma_color, int postprocess_window, double sigma_dist_fix, double sigma_color_fix, double occ_thr, int upscale_averaging_radius, double upscale_sigma_dist, double upscale_sigma_color, double speed_up_thr)

Ptr< DenseOpticalFlow >	createOptFlow_DualTVL1 ()

void	Rodrigues (InputArray src, OutputArray dst, OutputArray jacobian=noArray())
	converts rotation vector to rotation matrix or vice versa using Rodrigues transformation More...

Mat	findHomography (InputArray srcPoints, InputArray dstPoints, int method=0, double ransacReprojThreshold=3, OutputArray mask=noArray())
	computes the best-fit perspective transformation mapping srcPoints to dstPoints. More...

Mat	findHomography (InputArray srcPoints, InputArray dstPoints, OutputArray mask, int method=0, double ransacReprojThreshold=3)
	variant of findHomography for backward compatibility More...

Vec3d	RQDecomp3x3 (InputArray src, OutputArray mtxR, OutputArray mtxQ, OutputArray Qx=noArray(), OutputArray Qy=noArray(), OutputArray Qz=noArray())
	Computes RQ decomposition of 3x3 matrix. More...

void	decomposeProjectionMatrix (InputArray projMatrix, OutputArray cameraMatrix, OutputArray rotMatrix, OutputArray transVect, OutputArray rotMatrixX=noArray(), OutputArray rotMatrixY=noArray(), OutputArray rotMatrixZ=noArray(), OutputArray eulerAngles=noArray())
	Decomposes the projection matrix into camera matrix and the rotation martix and the translation vector. More...

void	matMulDeriv (InputArray A, InputArray B, OutputArray dABdA, OutputArray dABdB)
	computes derivatives of the matrix product w.r.t each of the multiplied matrix coefficients More...

void	composeRT (InputArray rvec1, InputArray tvec1, InputArray rvec2, InputArray tvec2, OutputArray rvec3, OutputArray tvec3, OutputArray dr3dr1=noArray(), OutputArray dr3dt1=noArray(), OutputArray dr3dr2=noArray(), OutputArray dr3dt2=noArray(), OutputArray dt3dr1=noArray(), OutputArray dt3dt1=noArray(), OutputArray dt3dr2=noArray(), OutputArray dt3dt2=noArray())
	composes 2 [R\|t] transformations together. Also computes the derivatives of the result w.r.t the arguments More...

void	projectPoints (InputArray objectPoints, InputArray rvec, InputArray tvec, InputArray cameraMatrix, InputArray distCoeffs, OutputArray imagePoints, OutputArray jacobian=noArray(), double aspectRatio=0)
	projects points from the model coordinate space to the image coordinates. Also computes derivatives of the image coordinates w.r.t the intrinsic and extrinsic camera parameters More...

bool	solvePnP (InputArray objectPoints, InputArray imagePoints, InputArray cameraMatrix, InputArray distCoeffs, OutputArray rvec, OutputArray tvec, bool useExtrinsicGuess=false, int flags=ITERATIVE)

void	solvePnPRansac (InputArray objectPoints, InputArray imagePoints, InputArray cameraMatrix, InputArray distCoeffs, OutputArray rvec, OutputArray tvec, bool useExtrinsicGuess=false, int iterationsCount=100, float reprojectionError=8.0, int minInliersCount=100, OutputArray inliers=noArray(), int flags=ITERATIVE)
	computes the camera pose from a few 3D points and the corresponding projections. The outliers are possible. More...

Mat	initCameraMatrix2D (InputArrayOfArrays objectPoints, InputArrayOfArrays imagePoints, Size imageSize, double aspectRatio=1.)
	initializes camera matrix from a few 3D points and the corresponding projections. More...

bool	findChessboardCorners (InputArray image, Size patternSize, OutputArray corners, int flags=CALIB_CB_ADAPTIVE_THRESH+CALIB_CB_NORMALIZE_IMAGE)
	finds checkerboard pattern of the specified size in the image More...

bool	find4QuadCornerSubpix (InputArray img, InputOutputArray corners, Size region_size)
	finds subpixel-accurate positions of the chessboard corners More...

void	drawChessboardCorners (InputOutputArray image, Size patternSize, InputArray corners, bool patternWasFound)
	draws the checkerboard pattern (found or partly found) in the image More...

bool	findCirclesGrid (InputArray image, Size patternSize, OutputArray centers, int flags=CALIB_CB_SYMMETRIC_GRID, const Ptr< FeatureDetector > &blobDetector=new SimpleBlobDetector())
	finds circles' grid pattern of the specified size in the image More...

bool	findCirclesGridDefault (InputArray image, Size patternSize, OutputArray centers, int flags=CALIB_CB_SYMMETRIC_GRID)
	the deprecated function. Use findCirclesGrid() instead of it. More...

double	calibrateCamera (InputArrayOfArrays objectPoints, InputArrayOfArrays imagePoints, Size imageSize, CV_OUT InputOutputArray cameraMatrix, CV_OUT InputOutputArray distCoeffs, OutputArrayOfArrays rvecs, OutputArrayOfArrays tvecs, int flags=0, TermCriteria criteria=TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, 30, DBL_EPSILON))
	finds intrinsic and extrinsic camera parameters from several fews of a known calibration pattern. More...

void	calibrationMatrixValues (InputArray cameraMatrix, Size imageSize, double apertureWidth, double apertureHeight, CV_OUT double &fovx, CV_OUT double &fovy, CV_OUT double &focalLength, CV_OUT Point2d &principalPoint, CV_OUT double &aspectRatio)
	computes several useful camera characteristics from the camera matrix, camera frame resolution and the physical sensor size. More...

double	stereoCalibrate (InputArrayOfArrays objectPoints, InputArrayOfArrays imagePoints1, InputArrayOfArrays imagePoints2, CV_OUT InputOutputArray cameraMatrix1, CV_OUT InputOutputArray distCoeffs1, CV_OUT InputOutputArray cameraMatrix2, CV_OUT InputOutputArray distCoeffs2, Size imageSize, OutputArray R, OutputArray T, OutputArray E, OutputArray F, TermCriteria criteria=TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, 30, 1e-6), int flags=CALIB_FIX_INTRINSIC)
	finds intrinsic and extrinsic parameters of a stereo camera More...

void	stereoRectify (InputArray cameraMatrix1, InputArray distCoeffs1, InputArray cameraMatrix2, InputArray distCoeffs2, Size imageSize, InputArray R, InputArray T, OutputArray R1, OutputArray R2, OutputArray P1, OutputArray P2, OutputArray Q, int flags=CALIB_ZERO_DISPARITY, double alpha=-1, Size newImageSize=Size(), CV_OUT Rect validPixROI1=0, CV_OUT Rect validPixROI2=0)
	computes the rectification transformation for a stereo camera from its intrinsic and extrinsic parameters More...

bool	stereoRectifyUncalibrated (InputArray points1, InputArray points2, InputArray F, Size imgSize, OutputArray H1, OutputArray H2, double threshold=5)
	computes the rectification transformation for an uncalibrated stereo camera (zero distortion is assumed) More...

float	rectify3Collinear (InputArray cameraMatrix1, InputArray distCoeffs1, InputArray cameraMatrix2, InputArray distCoeffs2, InputArray cameraMatrix3, InputArray distCoeffs3, InputArrayOfArrays imgpt1, InputArrayOfArrays imgpt3, Size imageSize, InputArray R12, InputArray T12, InputArray R13, InputArray T13, OutputArray R1, OutputArray R2, OutputArray R3, OutputArray P1, OutputArray P2, OutputArray P3, OutputArray Q, double alpha, Size newImgSize, CV_OUT Rect roi1, CV_OUT Rect roi2, int flags)
	computes the rectification transformations for 3-head camera, where all the heads are on the same line. More...

Mat	getOptimalNewCameraMatrix (InputArray cameraMatrix, InputArray distCoeffs, Size imageSize, double alpha, Size newImgSize=Size(), CV_OUT Rect *validPixROI=0, bool centerPrincipalPoint=false)
	returns the optimal new camera matrix More...

void	convertPointsToHomogeneous (InputArray src, OutputArray dst)
	converts point coordinates from normal pixel coordinates to homogeneous coordinates ((x,y)->(x,y,1)) More...

void	convertPointsFromHomogeneous (InputArray src, OutputArray dst)
	converts point coordinates from homogeneous to normal pixel coordinates ((x,y,z)->(x/z, y/z)) More...

void	convertPointsHomogeneous (InputArray src, OutputArray dst)
	for backward compatibility More...

Mat	findFundamentalMat (InputArray points1, InputArray points2, int method=FM_RANSAC, double param1=3., double param2=0.99, OutputArray mask=noArray())
	finds fundamental matrix from a set of corresponding 2D points More...

Mat	findFundamentalMat (InputArray points1, InputArray points2, OutputArray mask, int method=FM_RANSAC, double param1=3., double param2=0.99)
	variant of findFundamentalMat for backward compatibility More...

void	computeCorrespondEpilines (InputArray points, int whichImage, InputArray F, OutputArray lines)
	finds coordinates of epipolar lines corresponding the specified points More...

void	triangulatePoints (InputArray projMatr1, InputArray projMatr2, InputArray projPoints1, InputArray projPoints2, OutputArray points4D)

void	correctMatches (InputArray F, InputArray points1, InputArray points2, OutputArray newPoints1, OutputArray newPoints2)

void	filterSpeckles (InputOutputArray img, double newVal, int maxSpeckleSize, double maxDiff, InputOutputArray buf=noArray())
	filters off speckles (small regions of incorrectly computed disparity) More...

Rect	getValidDisparityROI (Rect roi1, Rect roi2, int minDisparity, int numberOfDisparities, int SADWindowSize)
	computes valid disparity ROI from the valid ROIs of the rectified images (that are returned by cv::stereoRectify()) More...

void	validateDisparity (InputOutputArray disparity, InputArray cost, int minDisparity, int numberOfDisparities, int disp12MaxDisp=1)
	validates disparity using the left-right check. The matrix "cost" should be computed by the stereo correspondence algorithm More...

void	reprojectImageTo3D (InputArray disparity, OutputArray _3dImage, InputArray Q, bool handleMissingValues=false, int ddepth=-1)
	reprojects disparity image to 3D: (x,y,d)->(X,Y,Z) using the matrix Q returned by cv::stereoRectify More...

int	estimateAffine3D (InputArray src, InputArray dst, OutputArray out, OutputArray inliers, double ransacThreshold=3, double confidence=0.99)

bool	initModule_features2d ()

void	write (FileStorage &fs, const string &name, const vector< KeyPoint > &keypoints)
	writes vector of keypoints to the file storage More...

void	read (const FileNode &node, CV_OUT vector< KeyPoint > &keypoints)
	reads vector of keypoints from the specified file storage node More...

void	FAST (InputArray image, CV_OUT vector< KeyPoint > &keypoints, int threshold, bool nonmaxSuppression=true)
	detects corners using FAST algorithm by E. Rosten More...

void	FASTX (InputArray image, CV_OUT vector< KeyPoint > &keypoints, int threshold, bool nonmaxSuppression, int type)

Mat	windowedMatchingMask (const vector< KeyPoint > &keypoints1, const vector< KeyPoint > &keypoints2, float maxDeltaX, float maxDeltaY)

void	drawKeypoints (const Mat &image, const vector< KeyPoint > &keypoints, CV_OUT Mat &outImage, const Scalar &color=Scalar::all(-1), int flags=DrawMatchesFlags::DEFAULT)

void	drawMatches (const Mat &img1, const vector< KeyPoint > &keypoints1, const Mat &img2, const vector< KeyPoint > &keypoints2, const vector< DMatch > &matches1to2, Mat &outImg, const Scalar &matchColor=Scalar::all(-1), const Scalar &singlePointColor=Scalar::all(-1), const vector< char > &matchesMask=vector< char >(), int flags=DrawMatchesFlags::DEFAULT)

void	drawMatches (const Mat &img1, const vector< KeyPoint > &keypoints1, const Mat &img2, const vector< KeyPoint > &keypoints2, const vector< vector< DMatch > > &matches1to2, Mat &outImg, const Scalar &matchColor=Scalar::all(-1), const Scalar &singlePointColor=Scalar::all(-1), const vector< vector< char > > &matchesMask=vector< vector< char > >(), int flags=DrawMatchesFlags::DEFAULT)

void	evaluateFeatureDetector (const Mat &img1, const Mat &img2, const Mat &H1to2, vector< KeyPoint > keypoints1, vector< KeyPoint > keypoints2, float &repeatability, int &correspCount, const Ptr< FeatureDetector > &fdetector=Ptr< FeatureDetector >())

void	computeRecallPrecisionCurve (const vector< vector< DMatch > > &matches1to2, const vector< vector< uchar > > &correctMatches1to2Mask, vector< Point2f > &recallPrecisionCurve)

float	getRecall (const vector< Point2f > &recallPrecisionCurve, float l_precision)

int	getNearestPoint (const vector< Point2f > &recallPrecisionCurve, float l_precision)

void	evaluateGenericDescriptorMatcher (const Mat &img1, const Mat &img2, const Mat &H1to2, vector< KeyPoint > &keypoints1, vector< KeyPoint > &keypoints2, vector< vector< DMatch > > matches1to2, vector< vector< uchar > > correctMatches1to2Mask, vector< Point2f > &recallPrecisionCurve, const Ptr< GenericDescriptorMatcher > &dmatch=Ptr< GenericDescriptorMatcher >())

void	groupRectangles (CV_OUT CV_IN_OUT vector< Rect > &rectList, int groupThreshold, double eps=0.2)

void	groupRectangles (CV_OUT CV_IN_OUT vector< Rect > &rectList, CV_OUT vector< int > &weights, int groupThreshold, double eps=0.2)

void	groupRectangles (vector< Rect > &rectList, int groupThreshold, double eps, vector< int > weights, vector< double > levelWeights)

void	groupRectangles (vector< Rect > &rectList, vector< int > &rejectLevels, vector< double > &levelWeights, int groupThreshold, double eps=0.2)

void	groupRectangles_meanshift (vector< Rect > &rectList, vector< double > &foundWeights, vector< double > &foundScales, double detectThreshold=0.0, Size winDetSize=Size(64, 128))

void	findDataMatrix (InputArray image, CV_OUT vector< string > &codes, OutputArray corners=noArray(), OutputArrayOfArrays dmtx=noArray())

void	drawDataMatrixCodes (InputOutputArray image, const vector< string > &codes, InputArray corners)

bool	initModule_ml (void)

void	inpaint (InputArray src, InputArray inpaintMask, OutputArray dst, double inpaintRadius, int flags)
	restores the damaged image areas using one of the available intpainting algorithms More...

void	fastNlMeansDenoising (InputArray src, OutputArray dst, float h=3, int templateWindowSize=7, int searchWindowSize=21)

void	fastNlMeansDenoisingColored (InputArray src, OutputArray dst, float h=3, float hColor=3, int templateWindowSize=7, int searchWindowSize=21)

void	fastNlMeansDenoisingMulti (InputArrayOfArrays srcImgs, OutputArray dst, int imgToDenoiseIndex, int temporalWindowSize, float h=3, int templateWindowSize=7, int searchWindowSize=21)

void	fastNlMeansDenoisingColoredMulti (InputArrayOfArrays srcImgs, OutputArray dst, int imgToDenoiseIndex, int temporalWindowSize, float h=3, float hColor=3, int templateWindowSize=7, int searchWindowSize=21)

bool	initModule_nonfree ()

std::ostream &	operator<< (std::ostream &out, const TickMeter &tm)

int	chamerMatching (Mat &img, Mat &templ, CV_OUT vector< vector< Point > > &results, CV_OUT vector< float > &cost, double templScale=1, int maxMatches=20, double minMatchDistance=1.0, int padX=3, int padY=3, int scales=5, double minScale=0.6, double maxScale=1.6, double orientationWeight=0.5, double truncate=20)

void	polyfit (const Mat &srcx, const Mat &srcy, Mat &dst, int order)

void	generateColors (std::vector< Scalar > &colors, size_t count, size_t factor=100)

bool	RGBDOdometry (Mat &Rt, const Mat &initRt, const Mat &image0, const Mat &depth0, const Mat &mask0, const Mat &image1, const Mat &depth1, const Mat &mask1, const Mat &cameraMatrix, float minDepth=0.f, float maxDepth=4.f, float maxDepthDiff=0.07f, const std::vector< int > &iterCounts=std::vector< int >(), const std::vector< float > &minGradientMagnitudes=std::vector< float >(), int transformType=RIGID_BODY_MOTION)

Mat	subspaceProject (InputArray W, InputArray mean, InputArray src)

Mat	subspaceReconstruct (InputArray W, InputArray mean, InputArray src)

Ptr< FaceRecognizer >	createEigenFaceRecognizer (int num_components=0, double threshold=DBL_MAX)

Ptr< FaceRecognizer >	createFisherFaceRecognizer (int num_components=0, double threshold=DBL_MAX)

Ptr< FaceRecognizer >	createLBPHFaceRecognizer (int radius=1, int neighbors=8, int grid_x=8, int grid_y=8, double threshold=DBL_MAX)

void	applyColorMap (InputArray src, OutputArray dst, int colormap)

bool	initModule_contrib ()

uchar *	getData (IplImage *image)

Variables
double	iterFactor =1.)

OutputArray	sum

OutputArray OutputArray	sqsum

OutputArray OutputArray int	sdepth =-1 )

OutputArray OutputArray OutputArray	tilted

OutputArray	dst

OutputArray OutputArray	labels

OutputArray OutputArray int	distanceType

OutputArray OutputArray int int	maskSize

OutputArray OutputArray int int int	labelType =DIST_LABEL_CCOMP )

Detailed Description

Namespace where all the C++ OpenCV functionality resides

Typedef Documentation

§ Affine3d

typedef Affine3<double> cv::Affine3d

§ Affine3f

typedef Affine3<float> cv::Affine3f

§ ANN_MLP_TrainParams

typedef CvANN_MLP_TrainParams cv::ANN_MLP_TrainParams

§ BinaryFunc

typedef void(* cv::BinaryFunc) (const uchar *src1, size_t step1, const uchar *src2, size_t step2, uchar *dst, size_t step, Size sz, void *)

§ Boost

typedef CvBoost cv::Boost

§ BoostParams

typedef CvBoostParams cv::BoostParams

§ BoostTree

typedef CvBoostTree cv::BoostTree

§ BundleAdjustCallback

typedef bool(* cv::BundleAdjustCallback) (int iteration, double norm_error, void *user_data)

§ ButtonCallback

typedef void(CV_CDECL * cv::ButtonCallback) (int state, void *userdata)

§ Complexd

typedef Complex<double> cv::Complexd

§ Complexf

typedef Complex<float> cv::Complexf

§ ConcurrentDoubleVector

typedef std::vector<double> cv::ConcurrentDoubleVector

§ ConcurrentRectVector

typedef std::vector<Rect> cv::ConcurrentRectVector

§ ConvertData

typedef void(* cv::ConvertData) (const void *from, void *to, int cn)

§ ConvertScaleData

typedef void(* cv::ConvertScaleData) (const void *from, void *to, int cn, double alpha, double beta)

§ DecisionTree

typedef CvDTree cv::DecisionTree

§ DTreeParams

typedef CvDTreeParams cv::DTreeParams

§ EMParams

typedef CvEMParams cv::EMParams

§ ErrorCallback

typedef int(CV_CDECL * cv::ErrorCallback) (int status, const char *func_name, const char *err_msg, const char *file_name, int line, void *userdata)

§ ERTree

typedef CvForestERTree cv::ERTree

§ ERTrees

typedef CvERTrees cv::ERTrees

§ ERTreeTRainData

typedef CvERTreeTrainData cv::ERTreeTRainData

§ ExpectationMaximization

typedef CvEM cv::ExpectationMaximization

§ FeatureTracker

typedef CvFeatureTracker cv::FeatureTracker

§ FeatureTrackerParams

typedef CvFeatureTrackerParams cv::FeatureTrackerParams

§ FernDescriptorMatch

typedef FernDescriptorMatcher cv::FernDescriptorMatch

§ ForestTree

typedef CvForestTree cv::ForestTree

§ GenericDescriptorMatch

typedef GenericDescriptorMatcher cv::GenericDescriptorMatch

§ GoodFeaturesToTrackDetector

typedef GFTTDetector cv::GoodFeaturesToTrackDetector

§ GradientBoostingTreeParams

typedef CvGBTreesParams cv::GradientBoostingTreeParams

§ GradientBoostingTrees

typedef CvGBTrees cv::GradientBoostingTrees

§ HammingLUT

typedef Hamming cv::HammingLUT

§ HybridTracker

typedef CvHybridTracker cv::HybridTracker

§ HybridTrackerParams

typedef CvHybridTrackerParams cv::HybridTrackerParams

§ InputArray

typedef const _InputArray& cv::InputArray

§ InputArrayOfArrays

typedef InputArray cv::InputArrayOfArrays

§ InputOutputArray

typedef OutputArray cv::InputOutputArray

§ InputOutputArrayOfArrays

typedef OutputArray cv::InputOutputArrayOfArrays

§ KNearest

typedef CvKNearest cv::KNearest

§ Mat1b

typedef Mat_<uchar> cv::Mat1b

§ Mat1d

typedef Mat_<double> cv::Mat1d

§ Mat1f

typedef Mat_<float> cv::Mat1f

§ Mat1i

typedef Mat_<int> cv::Mat1i

§ Mat1s

typedef Mat_<short> cv::Mat1s

§ Mat1w

typedef Mat_<ushort> cv::Mat1w

§ Mat2b

typedef Mat_<Vec2b> cv::Mat2b

§ Mat2d

typedef Mat_<Vec2d> cv::Mat2d

§ Mat2f

typedef Mat_<Vec2f> cv::Mat2f

§ Mat2i

typedef Mat_<Vec2i> cv::Mat2i

§ Mat2s

typedef Mat_<Vec2s> cv::Mat2s

§ Mat2w

typedef Mat_<Vec2w> cv::Mat2w

§ Mat3b

typedef Mat_<Vec3b> cv::Mat3b

§ Mat3d

typedef Mat_<Vec3d> cv::Mat3d

§ Mat3f

typedef Mat_<Vec3f> cv::Mat3f

§ Mat3i

typedef Mat_<Vec3i> cv::Mat3i

§ Mat3s

typedef Mat_<Vec3s> cv::Mat3s

§ Mat3w

typedef Mat_<Vec3w> cv::Mat3w

§ Mat4b

typedef Mat_<Vec4b> cv::Mat4b

§ Mat4d

typedef Mat_<Vec4d> cv::Mat4d

§ Mat4f

typedef Mat_<Vec4f> cv::Mat4f

§ Mat4i

typedef Mat_<Vec4i> cv::Mat4i

§ Mat4s

typedef Mat_<Vec4s> cv::Mat4s

§ Mat4w

typedef Mat_<Vec4w> cv::Mat4w

§ MatND

typedef Mat cv::MatND

§ Matx12d

typedef Matx<double, 1, 2> cv::Matx12d

§ Matx12f

typedef Matx<float, 1, 2> cv::Matx12f

§ Matx13d

typedef Matx<double, 1, 3> cv::Matx13d

§ Matx13f

typedef Matx<float, 1, 3> cv::Matx13f

§ Matx14d

typedef Matx<double, 1, 4> cv::Matx14d

§ Matx14f

typedef Matx<float, 1, 4> cv::Matx14f

§ Matx16d

typedef Matx<double, 1, 6> cv::Matx16d

§ Matx16f

typedef Matx<float, 1, 6> cv::Matx16f

§ Matx21d

typedef Matx<double, 2, 1> cv::Matx21d

§ Matx21f

typedef Matx<float, 2, 1> cv::Matx21f

§ Matx22d

typedef Matx<double, 2, 2> cv::Matx22d

§ Matx22f

typedef Matx<float, 2, 2> cv::Matx22f

§ Matx23d

typedef Matx<double, 2, 3> cv::Matx23d

§ Matx23f

typedef Matx<float, 2, 3> cv::Matx23f

§ Matx31d

typedef Matx<double, 3, 1> cv::Matx31d

§ Matx31f

typedef Matx<float, 3, 1> cv::Matx31f

§ Matx32d

typedef Matx<double, 3, 2> cv::Matx32d

§ Matx32f

typedef Matx<float, 3, 2> cv::Matx32f

§ Matx33d

typedef Matx<double, 3, 3> cv::Matx33d

§ Matx33f

typedef Matx<float, 3, 3> cv::Matx33f

§ Matx34d

typedef Matx<double, 3, 4> cv::Matx34d

§ Matx34f

typedef Matx<float, 3, 4> cv::Matx34f

§ Matx41d

typedef Matx<double, 4, 1> cv::Matx41d

§ Matx41f

typedef Matx<float, 4, 1> cv::Matx41f

§ Matx43d

typedef Matx<double, 4, 3> cv::Matx43d

§ Matx43f

typedef Matx<float, 4, 3> cv::Matx43f

§ Matx44d

typedef Matx<double, 4, 4> cv::Matx44d

§ Matx44f

typedef Matx<float, 4, 4> cv::Matx44f

§ Matx61d

typedef Matx<double, 6, 1> cv::Matx61d

§ Matx61f

typedef Matx<float, 6, 1> cv::Matx61f

§ Matx66d

typedef Matx<double, 6, 6> cv::Matx66d

§ Matx66f

typedef Matx<float, 6, 6> cv::Matx66f

§ MeanShiftTracker

typedef CvMeanShiftTracker cv::MeanShiftTracker

§ MeanShiftTrackerParams

typedef CvMeanShiftTrackerParams cv::MeanShiftTrackerParams

§ MemStorage

typedef Ptr<CvMemStorage> cv::MemStorage

§ MotionModel

typedef CvMotionModel cv::MotionModel

§ MouseCallback

typedef void(* cv::MouseCallback) (int event, int x, int y, int flags, void *userdata)

§ MserFeatureDetector

typedef MSER cv::MserFeatureDetector

§ NeuralNet_MLP

typedef CvANN_MLP cv::NeuralNet_MLP

§ NormalBayesClassifier

typedef CvNormalBayesClassifier cv::NormalBayesClassifier

§ OneWayDescriptorMatch

typedef OneWayDescriptorMatcher cv::OneWayDescriptorMatch

§ OpenGlDrawCallback

typedef void(* cv::OpenGlDrawCallback) (void *userdata)

§ OrbDescriptorExtractor

typedef ORB cv::OrbDescriptorExtractor

§ OrbFeatureDetector

typedef ORB cv::OrbFeatureDetector

§ OutputArray

typedef const _OutputArray& cv::OutputArray

§ OutputArrayOfArrays

typedef OutputArray cv::OutputArrayOfArrays

§ ParamGrid

typedef CvParamGrid cv::ParamGrid

§ Point

typedef Point2i cv::Point

§ Point2d

typedef Point_<double> cv::Point2d

§ Point2f

typedef Point_<float> cv::Point2f

§ Point2i

typedef Point_<int> cv::Point2i

§ Point2l

typedef Point_<int64> cv::Point2l

§ Point3d

typedef Point3_<double> cv::Point3d

§ Point3f

typedef Point3_<float> cv::Point3f

§ Point3i

typedef Point3_<int> cv::Point3i

§ RandomTreeParams

typedef CvRTParams cv::RandomTreeParams

§ RandomTrees

typedef CvRTrees cv::RandomTrees

§ Rect

typedef Rect_<int> cv::Rect

§ Scalar

typedef Scalar_<double> cv::Scalar

§ SiftDescriptorExtractor

typedef SIFT cv::SiftDescriptorExtractor

§ SiftFeatureDetector

typedef SIFT cv::SiftFeatureDetector

§ Size

typedef Size2i cv::Size

§ Size2d

typedef Size_<double> cv::Size2d

§ Size2f

typedef Size_<float> cv::Size2f

§ Size2i

typedef Size_<int> cv::Size2i

§ Size2l

typedef Size_<int64> cv::Size2l

§ StarFeatureDetector

typedef StarDetector cv::StarFeatureDetector

§ StatModel

typedef CvStatModel cv::StatModel

§ String

typedef std::string cv::String

§ SurfDescriptorExtractor

typedef SURF cv::SurfDescriptorExtractor

§ SurfFeatureDetector

typedef SURF cv::SurfFeatureDetector

§ SVM

typedef CvSVM cv::SVM

§ SVMKernel

typedef CvSVMKernel cv::SVMKernel

§ SVMParams

typedef CvSVMParams cv::SVMParams

§ SVMSolver

typedef CvSVMSolver cv::SVMSolver

§ TrackbarCallback

typedef void(CV_CDECL * cv::TrackbarCallback) (int pos, void *userdata)

§ TrainData

typedef CvMLData cv::TrainData

§ Vec2b

typedef Vec<uchar, 2> cv::Vec2b

§ Vec2d

typedef Vec<double, 2> cv::Vec2d

§ Vec2f

typedef Vec<float, 2> cv::Vec2f

§ Vec2i

typedef Vec<int, 2> cv::Vec2i

§ Vec2s

typedef Vec<short, 2> cv::Vec2s

§ Vec2w

typedef Vec<ushort, 2> cv::Vec2w

§ Vec3b

typedef Vec<uchar, 3> cv::Vec3b

§ Vec3d

typedef Vec<double, 3> cv::Vec3d

§ Vec3f

typedef Vec<float, 3> cv::Vec3f

§ Vec3i

typedef Vec<int, 3> cv::Vec3i

§ Vec3s

typedef Vec<short, 3> cv::Vec3s

§ Vec3w

typedef Vec<ushort, 3> cv::Vec3w

§ Vec4b

typedef Vec<uchar, 4> cv::Vec4b

§ Vec4d

typedef Vec<double, 4> cv::Vec4d

§ Vec4f

typedef Vec<float, 4> cv::Vec4f

§ Vec4i

typedef Vec<int, 4> cv::Vec4i

§ Vec4s

typedef Vec<short, 4> cv::Vec4s

§ Vec4w

typedef Vec<ushort, 4> cv::Vec4w

§ Vec6d

typedef Vec<double, 6> cv::Vec6d

§ Vec6f

typedef Vec<float, 6> cv::Vec6f

§ Vec6i

typedef Vec<int, 6> cv::Vec6i

§ Vec8i

typedef Vec<int, 8> cv::Vec8i

§ VectorDescriptorMatch

typedef VectorDescriptorMatcher cv::VectorDescriptorMatch

§ WImage1_16s

typedef WImageC<short, 1> cv::WImage1_16s

§ WImage1_16u

typedef WImageC<ushort, 1> cv::WImage1_16u

§ WImage1_b

typedef WImageC<uchar, 1> cv::WImage1_b

§ WImage1_f

typedef WImageC<float, 1> cv::WImage1_f

§ WImage3_16s

typedef WImageC<short, 3> cv::WImage3_16s

§ WImage3_16u

typedef WImageC<ushort, 3> cv::WImage3_16u

§ WImage3_b

typedef WImageC<uchar, 3> cv::WImage3_b

§ WImage3_f

typedef WImageC<float, 3> cv::WImage3_f

§ WImage_16s

typedef WImage<short> cv::WImage_16s

§ WImage_16u

typedef WImage<ushort> cv::WImage_16u

§ WImage_b

typedef WImage<uchar> cv::WImage_b

§ WImage_f

typedef WImage<float> cv::WImage_f

§ WImageBuffer1_16s

typedef WImageBufferC<short, 1> cv::WImageBuffer1_16s

§ WImageBuffer1_16u

typedef WImageBufferC<ushort, 1> cv::WImageBuffer1_16u

§ WImageBuffer1_b

typedef WImageBufferC<uchar, 1> cv::WImageBuffer1_b

§ WImageBuffer1_f

typedef WImageBufferC<float, 1> cv::WImageBuffer1_f

§ WImageBuffer3_16s

typedef WImageBufferC<short, 3> cv::WImageBuffer3_16s

§ WImageBuffer3_16u

typedef WImageBufferC<ushort, 3> cv::WImageBuffer3_16u

§ WImageBuffer3_b

typedef WImageBufferC<uchar, 3> cv::WImageBuffer3_b

§ WImageBuffer3_f

typedef WImageBufferC<float, 3> cv::WImageBuffer3_f

§ WImageBuffer_16s

typedef WImageBuffer<short> cv::WImageBuffer_16s

§ WImageBuffer_16u

typedef WImageBuffer<ushort> cv::WImageBuffer_16u

§ WImageBuffer_b

typedef WImageBuffer<uchar> cv::WImageBuffer_b

§ WImageBuffer_f

typedef WImageBuffer<float> cv::WImageBuffer_f

§ WImageView1_16s

typedef WImageViewC<short, 1> cv::WImageView1_16s

§ WImageView1_16u

typedef WImageViewC<ushort, 1> cv::WImageView1_16u

§ WImageView1_b

typedef WImageViewC<uchar, 1> cv::WImageView1_b

§ WImageView1_f

typedef WImageViewC<float, 1> cv::WImageView1_f

§ WImageView3_16s

typedef WImageViewC<short, 3> cv::WImageView3_16s

§ WImageView3_16u

typedef WImageViewC<ushort, 3> cv::WImageView3_16u

§ WImageView3_b

typedef WImageViewC<uchar, 3> cv::WImageView3_b

§ WImageView3_f

typedef WImageViewC<float, 3> cv::WImageView3_f

§ WImageView_16s

typedef WImageView<short> cv::WImageView_16s

§ WImageView_16u

typedef WImageView<ushort> cv::WImageView_16u

§ WImageView_b

typedef WImageView<uchar> cv::WImageView_b

§ WImageView_f

typedef WImageView<float> cv::WImageView_f

§ WString

typedef std::basic_string<wchar_t> cv::WString

§ YAPE

typedef LDetector cv::YAPE

Enumeration Type Documentation

§ anonymous enum

anonymous enum

Enumerator
MAGIC_MASK
TYPE_MASK
DEPTH_MASK

§ anonymous enum

anonymous enum

mode of the contour retrieval algorithm

Enumerator
RETR_EXTERNAL	retrieve only the most external (top-level) contours
RETR_LIST	retrieve all the contours without any hierarchical information
RETR_CCOMP	retrieve the connected components (that can possibly be nested)
RETR_TREE	retrieve all the contours and the whole hierarchy
RETR_FLOODFILL

§ anonymous enum

anonymous enum

the contour approximation algorithm

Enumerator
CHAIN_APPROX_NONE
CHAIN_APPROX_SIMPLE
CHAIN_APPROX_TC89_L1
CHAIN_APPROX_TC89_KCOS

§ anonymous enum

anonymous enum

Enumerator
SORT_EVERY_ROW
SORT_EVERY_COLUMN
SORT_ASCENDING
SORT_DESCENDING

§ anonymous enum

anonymous enum

Enumerator
COVAR_SCRAMBLED
COVAR_NORMAL
COVAR_USE_AVG
COVAR_SCALE
COVAR_ROWS
COVAR_COLS

§ anonymous enum

anonymous enum

Enumerator
WINDOW_NORMAL
WINDOW_AUTOSIZE
WINDOW_OPENGL
WND_PROP_FULLSCREEN
WND_PROP_AUTOSIZE
WND_PROP_ASPECT_RATIO
WND_PROP_OPENGL

§ anonymous enum

anonymous enum

Enumerator
EVENT_MOUSEMOVE
EVENT_LBUTTONDOWN
EVENT_RBUTTONDOWN
EVENT_MBUTTONDOWN
EVENT_LBUTTONUP
EVENT_RBUTTONUP
EVENT_MBUTTONUP
EVENT_LBUTTONDBLCLK
EVENT_RBUTTONDBLCLK
EVENT_MBUTTONDBLCLK

§ anonymous enum

anonymous enum

Enumerator
EVENT_FLAG_LBUTTON
EVENT_FLAG_RBUTTON
EVENT_FLAG_MBUTTON
EVENT_FLAG_CTRLKEY
EVENT_FLAG_SHIFTKEY
EVENT_FLAG_ALTKEY

§ anonymous enum

anonymous enum

Various k-Means flags

Enumerator
KMEANS_RANDOM_CENTERS
KMEANS_PP_CENTERS
KMEANS_USE_INITIAL_LABELS

§ anonymous enum

anonymous enum

Enumerator
IMREAD_UNCHANGED
IMREAD_GRAYSCALE
IMREAD_COLOR
IMREAD_ANYDEPTH
IMREAD_ANYCOLOR

§ anonymous enum

anonymous enum

Enumerator
IMWRITE_JPEG_QUALITY
IMWRITE_PNG_COMPRESSION
IMWRITE_PNG_STRATEGY
IMWRITE_PNG_BILEVEL
IMWRITE_PNG_STRATEGY_DEFAULT
IMWRITE_PNG_STRATEGY_FILTERED
IMWRITE_PNG_STRATEGY_HUFFMAN_ONLY
IMWRITE_PNG_STRATEGY_RLE
IMWRITE_PNG_STRATEGY_FIXED
IMWRITE_PXM_BINARY

§ anonymous enum

anonymous enum

Enumerator
FONT_HERSHEY_SIMPLEX
FONT_HERSHEY_PLAIN
FONT_HERSHEY_DUPLEX
FONT_HERSHEY_COMPLEX
FONT_HERSHEY_TRIPLEX
FONT_HERSHEY_COMPLEX_SMALL
FONT_HERSHEY_SCRIPT_SIMPLEX
FONT_HERSHEY_SCRIPT_COMPLEX
FONT_ITALIC

§ anonymous enum

anonymous enum

Enumerator
OPTFLOW_USE_INITIAL_FLOW
OPTFLOW_LK_GET_MIN_EIGENVALS
OPTFLOW_FARNEBACK_GAUSSIAN

§ anonymous enum

anonymous enum

type of the robust estimation algorithm

Enumerator
LMEDS	least-median algorithm
RANSAC	RANSAC algorithm.

§ anonymous enum

anonymous enum

computes the camera pose from a few 3D points and the corresponding projections. The outliers are not handled.

Enumerator
ITERATIVE
EPNP
P3P

§ anonymous enum

anonymous enum

Enumerator
CALIB_CB_ADAPTIVE_THRESH
CALIB_CB_NORMALIZE_IMAGE
CALIB_CB_FILTER_QUADS
CALIB_CB_FAST_CHECK

§ anonymous enum

anonymous enum

Enumerator
CALIB_CB_SYMMETRIC_GRID
CALIB_CB_ASYMMETRIC_GRID
CALIB_CB_CLUSTERING

§ anonymous enum

anonymous enum

Enumerator
CALIB_USE_INTRINSIC_GUESS
CALIB_FIX_ASPECT_RATIO
CALIB_FIX_PRINCIPAL_POINT
CALIB_ZERO_TANGENT_DIST
CALIB_FIX_FOCAL_LENGTH
CALIB_FIX_K1
CALIB_FIX_K2
CALIB_FIX_K3
CALIB_FIX_K4
CALIB_FIX_K5
CALIB_FIX_K6
CALIB_RATIONAL_MODEL
CALIB_FIX_INTRINSIC
CALIB_SAME_FOCAL_LENGTH
CALIB_ZERO_DISPARITY

§ anonymous enum

anonymous enum

the algorithm for finding fundamental matrix

Enumerator
FM_7POINT	7-point algorithm
FM_8POINT	8-point algorithm
FM_LMEDS	least-median algorithm
FM_RANSAC	RANSAC algorithm.

§ anonymous enum

anonymous enum

Enumerator
CASCADE_DO_CANNY_PRUNING
CASCADE_SCALE_IMAGE
CASCADE_FIND_BIGGEST_OBJECT
CASCADE_DO_ROUGH_SEARCH

§ anonymous enum

anonymous enum

the inpainting algorithm

Enumerator
INPAINT_NS
INPAINT_TELEA

§ anonymous enum

anonymous enum

Enumerator
ROTATION
TRANSLATION
RIGID_BODY_MOTION

§ anonymous enum

anonymous enum

Enumerator
COLORMAP_AUTUMN
COLORMAP_BONE
COLORMAP_JET
COLORMAP_WINTER
COLORMAP_RAINBOW
COLORMAP_OCEAN
COLORMAP_SUMMER
COLORMAP_SPRING
COLORMAP_COOL
COLORMAP_HSV
COLORMAP_PINK
COLORMAP_HOT

§ anonymous enum

anonymous enum

Enumerator
DECOMP_LU
DECOMP_SVD
DECOMP_EIG
DECOMP_CHOLESKY
DECOMP_QR
DECOMP_NORMAL

§ anonymous enum

anonymous enum

Enumerator
NORM_INF
NORM_L1
NORM_L2
NORM_L2SQR
NORM_HAMMING
NORM_HAMMING2
NORM_TYPE_MASK
NORM_RELATIVE
NORM_MINMAX

§ anonymous enum

anonymous enum

Enumerator
CMP_EQ
CMP_GT
CMP_GE
CMP_LT
CMP_LE
CMP_NE

§ anonymous enum

anonymous enum

Enumerator
GEMM_1_T
GEMM_2_T
GEMM_3_T

§ anonymous enum

anonymous enum

Enumerator
DFT_INVERSE
DFT_SCALE
DFT_ROWS
DFT_COMPLEX_OUTPUT
DFT_REAL_OUTPUT
DCT_INVERSE
DCT_ROWS

§ anonymous enum

anonymous enum

various border interpolation methods

Enumerator
BORDER_REPLICATE
BORDER_CONSTANT
BORDER_REFLECT
BORDER_WRAP
BORDER_REFLECT_101
BORDER_REFLECT101
BORDER_TRANSPARENT
BORDER_DEFAULT
BORDER_ISOLATED

§ anonymous enum

anonymous enum

type of the kernel

Enumerator
KERNEL_GENERAL
KERNEL_SYMMETRICAL
KERNEL_ASYMMETRICAL
KERNEL_SMOOTH
KERNEL_INTEGER

§ anonymous enum

anonymous enum

type of morphological operation

Enumerator
MORPH_ERODE
MORPH_DILATE
MORPH_OPEN
MORPH_CLOSE
MORPH_GRADIENT
MORPH_TOPHAT
MORPH_BLACKHAT
MORPH_HITMISS

§ anonymous enum

anonymous enum

shape of the structuring element

Enumerator
MORPH_RECT
MORPH_CROSS
MORPH_ELLIPSE

§ anonymous enum

anonymous enum

Enumerator
GHT_POSITION
GHT_SCALE
GHT_ROTATION

§ anonymous enum

anonymous enum

interpolation algorithm

Enumerator
INTER_NEAREST	nearest neighbor interpolation
INTER_LINEAR	bilinear interpolation
INTER_CUBIC	bicubic interpolation
INTER_AREA	area-based (or super) interpolation
INTER_LANCZOS4	Lanczos interpolation over 8x8 neighborhood.
INTER_MAX
WARP_INVERSE_MAP

§ anonymous enum

anonymous enum

Enumerator
DEPTH_MASK_8U
DEPTH_MASK_8S
DEPTH_MASK_16U
DEPTH_MASK_16S
DEPTH_MASK_32S
DEPTH_MASK_32F
DEPTH_MASK_64F
DEPTH_MASK_ALL
DEPTH_MASK_ALL_BUT_8S
DEPTH_MASK_FLT

§ anonymous enum

anonymous enum

Enumerator
INTER_BITS
INTER_BITS2
INTER_TAB_SIZE
INTER_TAB_SIZE2

§ anonymous enum

anonymous enum

type of the threshold operation

Enumerator
THRESH_BINARY
THRESH_BINARY_INV
THRESH_TRUNC
THRESH_TOZERO
THRESH_TOZERO_INV
THRESH_MASK
THRESH_OTSU

§ anonymous enum

anonymous enum

adaptive threshold algorithm

Enumerator
ADAPTIVE_THRESH_MEAN_C
ADAPTIVE_THRESH_GAUSSIAN_C

§ anonymous enum

anonymous enum

Enumerator
PROJ_SPHERICAL_ORTHO
PROJ_SPHERICAL_EQRECT

§ anonymous enum

anonymous enum

class of the pixel in GrabCut algorithm

Enumerator
GC_BGD	background
GC_FGD	foreground
GC_PR_BGD	most probably background
GC_PR_FGD	most probably foreground

§ anonymous enum

anonymous enum

GrabCut algorithm flags.

Enumerator
GC_INIT_WITH_RECT
GC_INIT_WITH_MASK
GC_EVAL

§ anonymous enum

anonymous enum

Enumerator
DIST_LABEL_CCOMP
DIST_LABEL_PIXEL

§ anonymous enum

anonymous enum

Enumerator
FLOODFILL_FIXED_RANGE
FLOODFILL_MASK_ONLY

§ anonymous enum

anonymous enum

Enumerator
COLOR_BGR2BGRA
COLOR_RGB2RGBA
COLOR_BGRA2BGR
COLOR_RGBA2RGB
COLOR_BGR2RGBA
COLOR_RGB2BGRA
COLOR_RGBA2BGR
COLOR_BGRA2RGB
COLOR_BGR2RGB
COLOR_RGB2BGR
COLOR_BGRA2RGBA
COLOR_RGBA2BGRA
COLOR_BGR2GRAY
COLOR_RGB2GRAY
COLOR_GRAY2BGR
COLOR_GRAY2RGB
COLOR_GRAY2BGRA
COLOR_GRAY2RGBA
COLOR_BGRA2GRAY
COLOR_RGBA2GRAY
COLOR_BGR2BGR565
COLOR_RGB2BGR565
COLOR_BGR5652BGR
COLOR_BGR5652RGB
COLOR_BGRA2BGR565
COLOR_RGBA2BGR565
COLOR_BGR5652BGRA
COLOR_BGR5652RGBA
COLOR_GRAY2BGR565
COLOR_BGR5652GRAY
COLOR_BGR2BGR555
COLOR_RGB2BGR555
COLOR_BGR5552BGR
COLOR_BGR5552RGB
COLOR_BGRA2BGR555
COLOR_RGBA2BGR555
COLOR_BGR5552BGRA
COLOR_BGR5552RGBA
COLOR_GRAY2BGR555
COLOR_BGR5552GRAY
COLOR_BGR2XYZ
COLOR_RGB2XYZ
COLOR_XYZ2BGR
COLOR_XYZ2RGB
COLOR_BGR2YCrCb
COLOR_RGB2YCrCb
COLOR_YCrCb2BGR
COLOR_YCrCb2RGB
COLOR_BGR2HSV
COLOR_RGB2HSV
COLOR_BGR2Lab
COLOR_RGB2Lab
COLOR_BayerBG2BGR
COLOR_BayerGB2BGR
COLOR_BayerRG2BGR
COLOR_BayerGR2BGR
COLOR_BayerBG2RGB
COLOR_BayerGB2RGB
COLOR_BayerRG2RGB
COLOR_BayerGR2RGB
COLOR_BGR2Luv
COLOR_RGB2Luv
COLOR_BGR2HLS
COLOR_RGB2HLS
COLOR_HSV2BGR
COLOR_HSV2RGB
COLOR_Lab2BGR
COLOR_Lab2RGB
COLOR_Luv2BGR
COLOR_Luv2RGB
COLOR_HLS2BGR
COLOR_HLS2RGB
COLOR_BayerBG2BGR_VNG
COLOR_BayerGB2BGR_VNG
COLOR_BayerRG2BGR_VNG
COLOR_BayerGR2BGR_VNG
COLOR_BayerBG2RGB_VNG
COLOR_BayerGB2RGB_VNG
COLOR_BayerRG2RGB_VNG
COLOR_BayerGR2RGB_VNG
COLOR_BGR2HSV_FULL
COLOR_RGB2HSV_FULL
COLOR_BGR2HLS_FULL
COLOR_RGB2HLS_FULL
COLOR_HSV2BGR_FULL
COLOR_HSV2RGB_FULL
COLOR_HLS2BGR_FULL
COLOR_HLS2RGB_FULL
COLOR_LBGR2Lab
COLOR_LRGB2Lab
COLOR_LBGR2Luv
COLOR_LRGB2Luv
COLOR_Lab2LBGR
COLOR_Lab2LRGB
COLOR_Luv2LBGR
COLOR_Luv2LRGB
COLOR_BGR2YUV
COLOR_RGB2YUV
COLOR_YUV2BGR
COLOR_YUV2RGB
COLOR_BayerBG2GRAY
COLOR_BayerGB2GRAY
COLOR_BayerRG2GRAY
COLOR_BayerGR2GRAY
COLOR_YUV2RGB_NV12
COLOR_YUV2BGR_NV12
COLOR_YUV2RGB_NV21
COLOR_YUV2BGR_NV21
COLOR_YUV420sp2RGB
COLOR_YUV420sp2BGR
COLOR_YUV2RGBA_NV12
COLOR_YUV2BGRA_NV12
COLOR_YUV2RGBA_NV21
COLOR_YUV2BGRA_NV21
COLOR_YUV420sp2RGBA
COLOR_YUV420sp2BGRA
COLOR_YUV2RGB_YV12
COLOR_YUV2BGR_YV12
COLOR_YUV2RGB_IYUV
COLOR_YUV2BGR_IYUV
COLOR_YUV2RGB_I420
COLOR_YUV2BGR_I420
COLOR_YUV420p2RGB
COLOR_YUV420p2BGR
COLOR_YUV2RGBA_YV12
COLOR_YUV2BGRA_YV12
COLOR_YUV2RGBA_IYUV
COLOR_YUV2BGRA_IYUV
COLOR_YUV2RGBA_I420
COLOR_YUV2BGRA_I420
COLOR_YUV420p2RGBA
COLOR_YUV420p2BGRA
COLOR_YUV2GRAY_420
COLOR_YUV2GRAY_NV21
COLOR_YUV2GRAY_NV12
COLOR_YUV2GRAY_YV12
COLOR_YUV2GRAY_IYUV
COLOR_YUV2GRAY_I420
COLOR_YUV420sp2GRAY
COLOR_YUV420p2GRAY
COLOR_YUV2RGB_UYVY
COLOR_YUV2BGR_UYVY
COLOR_YUV2RGB_Y422
COLOR_YUV2BGR_Y422
COLOR_YUV2RGB_UYNV
COLOR_YUV2BGR_UYNV
COLOR_YUV2RGBA_UYVY
COLOR_YUV2BGRA_UYVY
COLOR_YUV2RGBA_Y422
COLOR_YUV2BGRA_Y422
COLOR_YUV2RGBA_UYNV
COLOR_YUV2BGRA_UYNV
COLOR_YUV2RGB_YUY2
COLOR_YUV2BGR_YUY2
COLOR_YUV2RGB_YVYU
COLOR_YUV2BGR_YVYU
COLOR_YUV2RGB_YUYV
COLOR_YUV2BGR_YUYV
COLOR_YUV2RGB_YUNV
COLOR_YUV2BGR_YUNV
COLOR_YUV2RGBA_YUY2
COLOR_YUV2BGRA_YUY2
COLOR_YUV2RGBA_YVYU
COLOR_YUV2BGRA_YVYU
COLOR_YUV2RGBA_YUYV
COLOR_YUV2BGRA_YUYV
COLOR_YUV2RGBA_YUNV
COLOR_YUV2BGRA_YUNV
COLOR_YUV2GRAY_UYVY
COLOR_YUV2GRAY_YUY2
COLOR_YUV2GRAY_Y422
COLOR_YUV2GRAY_UYNV
COLOR_YUV2GRAY_YVYU
COLOR_YUV2GRAY_YUYV
COLOR_YUV2GRAY_YUNV
COLOR_RGBA2mRGBA
COLOR_mRGBA2RGBA
COLOR_RGB2YUV_I420
COLOR_BGR2YUV_I420
COLOR_RGB2YUV_IYUV
COLOR_BGR2YUV_IYUV
COLOR_RGBA2YUV_I420
COLOR_BGRA2YUV_I420
COLOR_RGBA2YUV_IYUV
COLOR_BGRA2YUV_IYUV
COLOR_RGB2YUV_YV12
COLOR_BGR2YUV_YV12
COLOR_RGBA2YUV_YV12
COLOR_BGRA2YUV_YV12
COLOR_COLORCVT_MAX

§ anonymous enum

anonymous enum

type of the template matching operation

Enumerator
TM_SQDIFF
TM_SQDIFF_NORMED
TM_CCORR
TM_CCORR_NORMED
TM_CCOEFF
TM_CCOEFF_NORMED

§ MarkerTypes

enum cv::MarkerTypes

Possible set of marker types used for the drawMarker function.

Enumerator
MARKER_CROSS
MARKER_TILTED_CROSS
MARKER_STAR
MARKER_DIAMOND
MARKER_SQUARE
MARKER_TRIANGLE_UP
MARKER_TRIANGLE_DOWN

§ RETINA_COLORSAMPLINGMETHOD

enum cv::RETINA_COLORSAMPLINGMETHOD

Enumerator
RETINA_COLOR_RANDOM	each pixel position is either R, G or B in a random choice
RETINA_COLOR_DIAGONAL	color sampling is RGBRGBRGB..., line 2 BRGBRGBRG..., line 3, GBRGBRGBR...
RETINA_COLOR_BAYER	standard bayer sampling

Function Documentation

§ abs() [1/2]

MatExpr cv::abs ( const Mat & m )

§ abs() [2/2]

MatExpr cv::abs ( const MatExpr & e )

§ absdiff()

void cv::absdiff	(	InputArray	src1,
		InputArray	src2,
		OutputArray	dst
	)

computes element-wise absolute difference of two arrays (dst = abs(src1 - src2))

§ accumulate()

void cv::accumulate	(	InputArray	src,
		InputOutputArray	dst,
		InputArray	mask = `noArray()`
	)

adds image to the accumulator (dst += src). Unlike cv::add, dst and src can have different types.

§ accumulateProduct()

void cv::accumulateProduct	(	InputArray	src1,
		InputArray	src2,
		InputOutputArray	dst,
		InputArray	mask = `noArray()`
	)

adds product of the 2 images to the accumulator (dst += src1*src2).

§ accumulateSquare()

void cv::accumulateSquare	(	InputArray	src,
		InputOutputArray	dst,
		InputArray	mask = `noArray()`
	)

adds squared src image to the accumulator (dst += src*src).

§ accumulateWeighted()

void cv::accumulateWeighted	(	InputArray	src,
		InputOutputArray	dst,
		double	alpha,
		InputArray	mask = `noArray()`
	)

updates the running average (dst = dst*(1-alpha) + src*alpha)

§ adaptiveBilateralFilter()

void cv::adaptiveBilateralFilter	(	InputArray	src,
		OutputArray	dst,
		Size	ksize,
		double	sigmaSpace,
		double	maxSigmaColor = `20.0`,
		Point	anchor = `Point(-1, -1)`,
		int	borderType = `BORDER_DEFAULT`
	)

smooths the image using adaptive bilateral filter

§ adaptiveThreshold()

void cv::adaptiveThreshold	(	InputArray	src,
		OutputArray	dst,
		double	maxValue,
		int	adaptiveMethod,
		int	thresholdType,
		int	blockSize,
		double	C
	)

applies variable (adaptive) threshold to the image

§ add()

void cv::add	(	InputArray	src1,
		InputArray	src2,
		OutputArray	dst,
		InputArray	mask = `noArray()`,
		int	dtype = `-1`
	)

adds one matrix to another (dst = src1 + src2)

§ addText()

void cv::addText	(	const Mat &	img,
		const string &	text,
		Point	org,
		CvFont	font
	)

§ addWeighted()

void cv::addWeighted	(	InputArray	src1,
		double	alpha,
		InputArray	src2,
		double	beta,
		double	gamma,
		OutputArray	dst,
		int	dtype = `-1`
	)

computes weighted sum of two arrays (dst = alpha*src1 + beta*src2 + gamma)

§ applyColorMap()

void cv::applyColorMap	(	InputArray	src,
		OutputArray	dst,
		int	colormap
	)

§ approxPolyDP()

void cv::approxPolyDP	(	InputArray	curve,
		OutputArray	approxCurve,
		double	epsilon,
		bool	closed
	)

approximates contour or a curve using Douglas-Peucker algorithm

§ arcLength()

double cv::arcLength	(	InputArray	curve,
		bool	closed
	)

computes the contour perimeter (closed=true) or a curve length

§ arrowedLine()

void cv::arrowedLine	(	CV_IN_OUT Mat &	img,
		Point	pt1,
		Point	pt2,
		const Scalar &	color,
		int	thickness = `1`,
		int	line_type = `8`,
		int	shift = `0`,
		double	tipLength = `0.1`
	)

draws an arrow from pt1 to pt2 in the image

§ batchDistance()

void cv::batchDistance	(	InputArray	src1,
		InputArray	src2,
		OutputArray	dist,
		int	dtype,
		OutputArray	nidx,
		int	normType = `NORM_L2`,
		int	K = `0`,
		InputArray	mask = `noArray()`,
		int	update = `0`,
		bool	crosscheck = `false`
	)

naive nearest neighbor finder

§ bilateralFilter()

void cv::bilateralFilter	(	InputArray	src,
		OutputArray	dst,
		int	d,
		double	sigmaColor,
		double	sigmaSpace,
		int	borderType = `BORDER_DEFAULT`
	)

smooths the image using bilateral filter

§ bitwise_and()

void cv::bitwise_and	(	InputArray	src1,
		InputArray	src2,
		OutputArray	dst,
		InputArray	mask = `noArray()`
	)

computes bitwise conjunction of the two arrays (dst = src1 & src2)

§ bitwise_not()

void cv::bitwise_not	(	InputArray	src,
		OutputArray	dst,
		InputArray	mask = `noArray()`
	)

inverts each bit of array (dst = ~src)

§ bitwise_or()

void cv::bitwise_or	(	InputArray	src1,
		InputArray	src2,
		OutputArray	dst,
		InputArray	mask = `noArray()`
	)

computes bitwise disjunction of the two arrays (dst = src1 | src2)

§ bitwise_xor()

void cv::bitwise_xor	(	InputArray	src1,
		InputArray	src2,
		OutputArray	dst,
		InputArray	mask = `noArray()`
	)

computes bitwise exclusive-or of the two arrays (dst = src1 ^ src2)

§ blur()

void cv::blur	(	InputArray	src,
		OutputArray	dst,
		Size	ksize,
		Point	anchor = `Point(-1,-1)`,
		int	borderType = `BORDER_DEFAULT`
	)

a synonym for normalized box filter

§ borderInterpolate()

int cv::borderInterpolate	(	int	p,
		int	len,
		int	borderType
	)

1D interpolation function: returns coordinate of the "donor" pixel for the specified location p.

§ boundingRect()

Rect cv::boundingRect ( InputArray points )

computes the bounding rectangle for a contour

§ boxFilter()

void cv::boxFilter	(	InputArray	src,
		OutputArray	dst,
		int	ddepth,
		Size	ksize,
		Point	anchor = `Point(-1,-1)`,
		bool	normalize = `true`,
		int	borderType = `BORDER_DEFAULT`
	)

smooths the image using the box filter. Each pixel is processed in O(1) time

§ buildOpticalFlowPyramid()

int cv::buildOpticalFlowPyramid	(	InputArray	img,
		OutputArrayOfArrays	pyramid,
		Size	winSize,
		int	maxLevel,
		bool	withDerivatives = `true`,
		int	pyrBorder = `BORDER_REFLECT_101`,
		int	derivBorder = `BORDER_CONSTANT`,
		bool	tryReuseInputImage = `true`
	)

constructs a pyramid which can be used as input for calcOpticalFlowPyrLK

§ buildPyramid()

void cv::buildPyramid	(	InputArray	src,
		OutputArrayOfArrays	dst,
		int	maxlevel,
		int	borderType = `BORDER_DEFAULT`
	)

builds the gaussian pyramid using pyrDown() as a basic operation

§ calcBackProject() [1/3]

void cv::calcBackProject	(	const Mat *	images,
		int	nimages,
		const int *	channels,
		InputArray	hist,
		OutputArray	backProject,
		const float **	ranges,
		double	scale = `1`,
		bool	uniform = `true`
	)

computes back projection for the set of images

§ calcBackProject() [2/3]

void cv::calcBackProject	(	const Mat *	images,
		int	nimages,
		const int *	channels,
		const SparseMat &	hist,
		OutputArray	backProject,
		const float **	ranges,
		double	scale = `1`,
		bool	uniform = `true`
	)

computes back projection for the set of images

§ calcBackProject() [3/3]

void cv::calcBackProject	(	InputArrayOfArrays	images,
		const vector< int > &	channels,
		InputArray	hist,
		OutputArray	dst,
		const vector< float > &	ranges,
		double	scale
	)

§ calcCovarMatrix() [1/2]

void cv::calcCovarMatrix	(	const Mat *	samples,
		int	nsamples,
		Mat &	covar,
		Mat &	mean,
		int	flags,
		int	ctype = `CV_64F`
	)

computes covariation matrix of a set of samples

§ calcCovarMatrix() [2/2]

void cv::calcCovarMatrix	(	InputArray	samples,
		OutputArray	covar,
		OutputArray	mean,
		int	flags,
		int	ctype = `CV_64F`
	)

computes covariation matrix of a set of samples

§ calcGlobalOrientation()

double cv::calcGlobalOrientation	(	InputArray	orientation,
		InputArray	mask,
		InputArray	mhi,
		double	timestamp,
		double	duration
	)

computes the global orientation of the selected motion history image part

§ calcHist() [1/3]

void cv::calcHist	(	const Mat *	images,
		int	nimages,
		const int *	channels,
		InputArray	mask,
		OutputArray	hist,
		int	dims,
		const int *	histSize,
		const float **	ranges,
		bool	uniform = `true`,
		bool	accumulate = `false`
	)

computes the joint dense histogram for a set of images.

§ calcHist() [2/3]

void cv::calcHist	(	const Mat *	images,
		int	nimages,
		const int *	channels,
		InputArray	mask,
		SparseMat &	hist,
		int	dims,
		const int *	histSize,
		const float **	ranges,
		bool	uniform = `true`,
		bool	accumulate = `false`
	)

computes the joint sparse histogram for a set of images.

§ calcHist() [3/3]

void cv::calcHist	(	InputArrayOfArrays	images,
		const vector< int > &	channels,
		InputArray	mask,
		OutputArray	hist,
		const vector< int > &	histSize,
		const vector< float > &	ranges,
		bool	accumulate = `false`
	)

§ calcMotionGradient()

void cv::calcMotionGradient	(	InputArray	mhi,
		OutputArray	mask,
		OutputArray	orientation,
		double	delta1,
		double	delta2,
		int	apertureSize = `3`
	)

computes the motion gradient orientation image from the motion history image

§ calcOpticalFlowFarneback()

void cv::calcOpticalFlowFarneback	(	InputArray	prev,
		InputArray	next,
		CV_OUT InputOutputArray	flow,
		double	pyr_scale,
		int	levels,
		int	winsize,
		int	iterations,
		int	poly_n,
		double	poly_sigma,
		int	flags
	)

computes dense optical flow using Farneback algorithm

§ calcOpticalFlowPyrLK()

void cv::calcOpticalFlowPyrLK	(	InputArray	prevImg,
		InputArray	nextImg,
		InputArray	prevPts,
		CV_OUT InputOutputArray	nextPts,
		OutputArray	status,
		OutputArray	err,
		Size	winSize = `Size(21, 21)`,
		int	maxLevel = `3`,
		TermCriteria	criteria = `TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, 30, 0.01)`,
		int	flags = `0`,
		double	minEigThreshold = `1e-4`
	)

computes sparse optical flow using multi-scale Lucas-Kanade algorithm

§ calcOpticalFlowSF() [1/2]

void cv::calcOpticalFlowSF	(	Mat &	from,
		Mat &	to,
		Mat &	flow,
		int	layers,
		int	averaging_block_size,
		int	max_flow
	)

computes dense optical flow using Simple Flow algorithm

§ calcOpticalFlowSF() [2/2]

void cv::calcOpticalFlowSF	(	Mat &	from,
		Mat &	to,
		Mat &	flow,
		int	layers,
		int	averaging_block_size,
		int	max_flow,
		double	sigma_dist,
		double	sigma_color,
		int	postprocess_window,
		double	sigma_dist_fix,
		double	sigma_color_fix,
		double	occ_thr,
		int	upscale_averaging_radius,
		double	upscale_sigma_dist,
		double	upscale_sigma_color,
		double	speed_up_thr
	)

§ calibrateCamera()

double cv::calibrateCamera	(	InputArrayOfArrays	objectPoints,
		InputArrayOfArrays	imagePoints,
		Size	imageSize,
		CV_OUT InputOutputArray	cameraMatrix,
		CV_OUT InputOutputArray	distCoeffs,
		OutputArrayOfArrays	rvecs,
		OutputArrayOfArrays	tvecs,
		int	flags = `0`,
		TermCriteria	criteria = `TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, 30, DBL_EPSILON)`
	)

finds intrinsic and extrinsic camera parameters from several fews of a known calibration pattern.

§ calibrationMatrixValues()

void cv::calibrationMatrixValues	(	InputArray	cameraMatrix,
		Size	imageSize,
		double	apertureWidth,
		double	apertureHeight,
		CV_OUT double &	fovx,
		CV_OUT double &	fovy,
		CV_OUT double &	focalLength,
		CV_OUT Point2d &	principalPoint,
		CV_OUT double &	aspectRatio
	)

computes several useful camera characteristics from the camera matrix, camera frame resolution and the physical sensor size.

§ CamShift()

RotatedRect cv::CamShift	(	InputArray	probImage,
		CV_OUT CV_IN_OUT Rect &	window,
		TermCriteria	criteria
	)

updates the object tracking window using CAMSHIFT algorithm

§ Canny()

void cv::Canny	(	InputArray	image,
		OutputArray	edges,
		double	threshold1,
		double	threshold2,
		int	apertureSize = `3`,
		bool	L2gradient = `false`
	)

applies Canny edge detector and produces the edge map.

§ cartToPolar()

void cv::cartToPolar	(	InputArray	x,
		InputArray	y,
		OutputArray	magnitude,
		OutputArray	angle,
		bool	angleInDegrees = `false`
	)

converts Cartesian coordinates to polar

§ chamerMatching()

int cv::chamerMatching	(	Mat &	img,
		Mat &	templ,
		CV_OUT vector< vector< Point > > &	results,
		CV_OUT vector< float > &	cost,
		double	templScale = `1`,
		int	maxMatches = `20`,
		double	minMatchDistance = `1.0`,
		int	padX = `3`,
		int	padY = `3`,
		int	scales = `5`,
		double	minScale = `0.6`,
		double	maxScale = `1.6`,
		double	orientationWeight = `0.5`,
		double	truncate = `20`
	)

§ checkHardwareSupport()

bool cv::checkHardwareSupport ( int feature )

Returns SSE etc. support status

The function returns true if certain hardware features are available. Currently, the following features are recognized:

CV_CPU_MMX - MMX
CV_CPU_SSE - SSE
CV_CPU_SSE2 - SSE 2
CV_CPU_SSE3 - SSE 3
CV_CPU_SSSE3 - SSSE 3
CV_CPU_SSE4_1 - SSE 4.1
CV_CPU_SSE4_2 - SSE 4.2
CV_CPU_POPCNT - POPCOUNT
CV_CPU_AVX - AVX
CV_CPU_AVX2 - AVX2

Note: {Note that the function output is not static. Once you called cv::useOptimized(false), most of the hardware acceleration is disabled and thus the function will returns false, until you call cv::useOptimized(true)}

§ checkRange()

bool cv::checkRange	(	InputArray	a,
		bool	quiet = `true`,
		CV_OUT Point *	pos = `0`,
		double	minVal = `-DBL_MAX`,
		double	maxVal = `DBL_MAX`
	)

checks that each matrix element is within the specified range.

§ Cholesky() [1/2]

bool cv::Cholesky	(	float *	A,
		size_t	astep,
		int	m,
		float *	b,
		size_t	bstep,
		int	n
	)

§ Cholesky() [2/2]

bool cv::Cholesky	(	double *	A,
		size_t	astep,
		int	m,
		double *	b,
		size_t	bstep,
		int	n
	)

§ circle()

void cv::circle	(	CV_IN_OUT Mat &	img,
		Point	center,
		int	radius,
		const Scalar &	color,
		int	thickness = `1`,
		int	lineType = `8`,
		int	shift = `0`
	)

draws the circle outline or a solid circle in the image

§ clearSeq()

void cv::clearSeq ( CvSeq * seq )

§ clipLine() [1/3]

bool cv::clipLine	(	Size	imgSize,
		CV_IN_OUT Point &	pt1,
		CV_IN_OUT Point &	pt2
	)

clips the line segment by the rectangle Rect(0, 0, imgSize.width, imgSize.height)

§ clipLine() [2/3]

bool cv::clipLine	(	Size2l	imgSize,
		CV_IN_OUT Point2l &	pt1,
		CV_IN_OUT Point2l &	pt2
	)

§ clipLine() [3/3]

bool cv::clipLine	(	Rect	imgRect,
		CV_OUT CV_IN_OUT Point &	pt1,
		CV_OUT CV_IN_OUT Point &	pt2
	)

clips the line segment by the rectangle imgRect

§ CommandLineParser::analyzeValue< std::string >()

template<>

std::string cv::CommandLineParser::analyzeValue< std::string >	(	const std::string &	str,
		bool	space_delete
	)

§ compare()

void cv::compare	(	InputArray	src1,
		InputArray	src2,
		OutputArray	dst,
		int	cmpop
	)

compares elements of two arrays (dst = src1 <cmpop> src2)

§ compareHist() [1/2]

double cv::compareHist	(	InputArray	H1,
		InputArray	H2,
		int	method
	)

compares two histograms stored in dense arrays

§ compareHist() [2/2]

double cv::compareHist	(	const SparseMat &	H1,
		const SparseMat &	H2,
		int	method
	)

compares two histograms stored in sparse arrays

§ completeSymm()

void cv::completeSymm	(	InputOutputArray	mtx,
		bool	lowerToUpper = `false`
	)

extends the symmetrical matrix from the lower half or from the upper half

§ composeRT()

void cv::composeRT	(	InputArray	rvec1,
		InputArray	tvec1,
		InputArray	rvec2,
		InputArray	tvec2,
		OutputArray	rvec3,
		OutputArray	tvec3,
		OutputArray	dr3dr1 = `noArray()`,
		OutputArray	dr3dt1 = `noArray()`,
		OutputArray	dr3dr2 = `noArray()`,
		OutputArray	dr3dt2 = `noArray()`,
		OutputArray	dt3dr1 = `noArray()`,
		OutputArray	dt3dt1 = `noArray()`,
		OutputArray	dt3dr2 = `noArray()`,
		OutputArray	dt3dt2 = `noArray()`
	)

composes 2 [R|t] transformations together. Also computes the derivatives of the result w.r.t the arguments

§ computeCorrespondEpilines()

void cv::computeCorrespondEpilines	(	InputArray	points,
		int	whichImage,
		InputArray	F,
		OutputArray	lines
	)

finds coordinates of epipolar lines corresponding the specified points

§ computeRecallPrecisionCurve()

void cv::computeRecallPrecisionCurve	(	const vector< vector< DMatch > > &	matches1to2,
		const vector< vector< uchar > > &	correctMatches1to2Mask,
		vector< Point2f > &	recallPrecisionCurve
	)

§ conjugate() [1/2]

template<typename _Tp >

Vec<_Tp, 2> cv::conjugate ( const Vec< _Tp, 2 > & v )

§ conjugate() [2/2]

template<typename _Tp >

Vec<_Tp, 4> cv::conjugate ( const Vec< _Tp, 4 > & v )

§ contourArea()

double cv::contourArea	(	InputArray	contour,
		bool	oriented = `false`
	)

computes the contour area

§ convertMaps()

void cv::convertMaps	(	InputArray	map1,
		InputArray	map2,
		OutputArray	dstmap1,
		OutputArray	dstmap2,
		int	dstmap1type,
		bool	nninterpolation = `false`
	)

converts maps for remap from floating-point to fixed-point format or backwards

§ convertPointsFromHomogeneous()

void cv::convertPointsFromHomogeneous	(	InputArray	src,
		OutputArray	dst
	)

converts point coordinates from homogeneous to normal pixel coordinates ((x,y,z)->(x/z, y/z))

§ convertPointsHomogeneous()

void cv::convertPointsHomogeneous	(	InputArray	src,
		OutputArray	dst
	)

for backward compatibility

§ convertPointsToHomogeneous()

void cv::convertPointsToHomogeneous	(	InputArray	src,
		OutputArray	dst
	)

converts point coordinates from normal pixel coordinates to homogeneous coordinates ((x,y)->(x,y,1))

§ convertScaleAbs()

void cv::convertScaleAbs	(	InputArray	src,
		OutputArray	dst,
		double	alpha = `1`,
		double	beta = `0`
	)

scales array elements, computes absolute values and converts the results to 8-bit unsigned integers: dst(i)=saturate_cast<uchar>abs(src(i)*alpha+beta)

§ convexHull()

void cv::convexHull	(	InputArray	points,
		OutputArray	hull,
		bool	clockwise = `false`,
		bool	returnPoints = `true`
	)

computes convex hull for a set of 2D points.

§ convexityDefects()

void cv::convexityDefects	(	InputArray	contour,
		InputArray	convexhull,
		OutputArray	convexityDefects
	)

computes the contour convexity defects

§ copyMakeBorder()

void cv::copyMakeBorder	(	InputArray	src,
		OutputArray	dst,
		int	top,
		int	bottom,
		int	left,
		int	right,
		int	borderType,
		const Scalar &	value = `Scalar()`
	)

copies 2D array to a larger destination array with extrapolation of the outer part of src using the specified border mode

§ cornerEigenValsAndVecs()

void cv::cornerEigenValsAndVecs	(	InputArray	src,
		OutputArray	dst,
		int	blockSize,
		int	ksize,
		int	borderType = `BORDER_DEFAULT`
	)

computes both eigenvalues and the eigenvectors of 2x2 derivative covariation matrix at each pixel. The output is stored as 6-channel matrix.

§ cornerHarris()

void cv::cornerHarris	(	InputArray	src,
		OutputArray	dst,
		int	blockSize,
		int	ksize,
		double	k,
		int	borderType = `BORDER_DEFAULT`
	)

computes Harris cornerness criteria at each image pixel

§ cornerMinEigenVal()

void cv::cornerMinEigenVal	(	InputArray	src,
		OutputArray	dst,
		int	blockSize,
		int	ksize = `3`,
		int	borderType = `BORDER_DEFAULT`
	)

computes minimum eigen value of 2x2 derivative covariation matrix at each pixel - the cornerness criteria

§ cornerSubPix()

void cv::cornerSubPix	(	InputArray	image,
		InputOutputArray	corners,
		Size	winSize,
		Size	zeroZone,
		TermCriteria	criteria
	)

adjusts the corner locations with sub-pixel accuracy to maximize the certain cornerness criteria

§ correctMatches()

void cv::correctMatches	(	InputArray	F,
		InputArray	points1,
		InputArray	points2,
		OutputArray	newPoints1,
		OutputArray	newPoints2
	)

§ countNonZero()

int cv::countNonZero ( InputArray src )

computes the number of nonzero array elements

§ createBoxFilter()

Ptr<FilterEngine> cv::createBoxFilter	(	int	srcType,
		int	dstType,
		Size	ksize,
		Point	anchor = `Point(-1,-1)`,
		bool	normalize = `true`,
		int	borderType = `BORDER_DEFAULT`
	)

returns box filter engine

§ createButton()

int cv::createButton	(	const string &	bar_name,
		ButtonCallback	on_change,
		void *	userdata = `NULL`,
		int	type = `CV_PUSH_BUTTON`,
		bool	initial_button_state = `0`
	)

§ createCLAHE()

Ptr<CLAHE> cv::createCLAHE	(	double	clipLimit = `40.0`,
		Size	tileGridSize = `Size(8, 8)`
	)

§ createDerivFilter()

Ptr<FilterEngine> cv::createDerivFilter	(	int	srcType,
		int	dstType,
		int	dx,
		int	dy,
		int	ksize,
		int	borderType = `BORDER_DEFAULT`
	)

returns filter engine for the generalized Sobel operator

§ createEigenFaceRecognizer()

Ptr<FaceRecognizer> cv::createEigenFaceRecognizer	(	int	num_components = `0`,
		double	threshold = `DBL_MAX`
	)

§ createFisherFaceRecognizer()

Ptr<FaceRecognizer> cv::createFisherFaceRecognizer	(	int	num_components = `0`,
		double	threshold = `DBL_MAX`
	)

§ createGaussianFilter()

Ptr<FilterEngine> cv::createGaussianFilter	(	int	type,
		Size	ksize,
		double	sigma1,
		double	sigma2 = `0`,
		int	borderType = `BORDER_DEFAULT`
	)

returns the Gaussian filter engine

§ createHanningWindow()

void cv::createHanningWindow	(	OutputArray	dst,
		Size	winSize,
		int	type
	)

§ createLBPHFaceRecognizer()

Ptr<FaceRecognizer> cv::createLBPHFaceRecognizer	(	int	radius = `1`,
		int	neighbors = `8`,
		int	grid_x = `8`,
		int	grid_y = `8`,
		double	threshold = `DBL_MAX`
	)

§ createLinearFilter()

Ptr<FilterEngine> cv::createLinearFilter	(	int	srcType,
		int	dstType,
		InputArray	kernel,
		Point	_anchor = `Point(-1,-1)`,
		double	delta = `0`,
		int	rowBorderType = `BORDER_DEFAULT`,
		int	columnBorderType = `-1`,
		const Scalar &	borderValue = `Scalar()`
	)

returns the non-separable linear filter engine

§ createMorphologyFilter()

Ptr<FilterEngine> cv::createMorphologyFilter	(	int	op,
		int	type,
		InputArray	kernel,
		Point	anchor = `Point(-1,-1)`,
		int	rowBorderType = `BORDER_CONSTANT`,
		int	columnBorderType = `-1`,
		const Scalar &	borderValue = `morphologyDefaultBorderValue()`
	)

returns morphological filter engine. Only MORPH_ERODE and MORPH_DILATE are supported.

§ createOptFlow_DualTVL1()

Ptr<DenseOpticalFlow> cv::createOptFlow_DualTVL1 ( )

§ createSeparableLinearFilter()

Ptr<FilterEngine> cv::createSeparableLinearFilter	(	int	srcType,
		int	dstType,
		InputArray	rowKernel,
		InputArray	columnKernel,
		Point	anchor = `Point(-1,-1)`,
		double	delta = `0`,
		int	rowBorderType = `BORDER_DEFAULT`,
		int	columnBorderType = `-1`,
		const Scalar &	borderValue = `Scalar()`
	)

returns the separable linear filter engine

§ createTrackbar()

int cv::createTrackbar	(	const string &	trackbarname,
		const string &	winname,
		int *	value,
		int	count,
		TrackbarCallback	onChange = `0`,
		void *	userdata = `0`
	)

§ cubeRoot()

float cv::cubeRoot ( float val )

computes cube root of the argument

§ currentParallelFramework()

const char* cv::currentParallelFramework ( )

§ cv2eigen() [1/8]

template<typename _Tp , int _rows, int _cols, int _options, int _maxRows, int _maxCols>

void cv::cv2eigen	(	const Mat &	src,
		Eigen::Matrix< _Tp, _rows, _cols, _options, _maxRows, _maxCols > &	dst
	)

§ cv2eigen() [2/8]

template<typename _Tp , int _rows, int _cols, int _options, int _maxRows, int _maxCols>

void cv::cv2eigen	(	const Matx< _Tp, _rows, _cols > &	src,
		Eigen::Matrix< _Tp, _rows, _cols, _options, _maxRows, _maxCols > &	dst
	)

§ cv2eigen() [3/8]

template<typename _Tp >

void cv::cv2eigen	(	const Mat &	src,
		Eigen::Matrix< _Tp, Eigen::Dynamic, Eigen::Dynamic > &	dst
	)

§ cv2eigen() [4/8]

template<typename _Tp , int _rows, int _cols>

void cv::cv2eigen	(	const Matx< _Tp, _rows, _cols > &	src,
		Eigen::Matrix< _Tp, Eigen::Dynamic, Eigen::Dynamic > &	dst
	)

§ cv2eigen() [5/8]

template<typename _Tp >

void cv::cv2eigen	(	const Mat &	src,
		Eigen::Matrix< _Tp, Eigen::Dynamic, 1 > &	dst
	)

§ cv2eigen() [6/8]

template<typename _Tp , int _rows>

void cv::cv2eigen	(	const Matx< _Tp, _rows, 1 > &	src,
		Eigen::Matrix< _Tp, Eigen::Dynamic, 1 > &	dst
	)

§ cv2eigen() [7/8]

template<typename _Tp >

void cv::cv2eigen	(	const Mat &	src,
		Eigen::Matrix< _Tp, 1, Eigen::Dynamic > &	dst
	)

§ cv2eigen() [8/8]

template<typename _Tp , int _cols>

void cv::cv2eigen	(	const Matx< _Tp, 1, _cols > &	src,
		Eigen::Matrix< _Tp, 1, Eigen::Dynamic > &	dst
	)

§ CV_EXPORTS_AS() [1/5]

cv::CV_EXPORTS_AS ( integral2 )

computes the integral image and integral for the squared image

§ CV_EXPORTS_AS() [2/5]

cv::CV_EXPORTS_AS ( integral3 )

computes the integral image, integral for the squared image and the tilted integral image

§ CV_EXPORTS_AS() [3/5]

cv::CV_EXPORTS_AS ( distanceTransformWithLabels )

builds the discrete Voronoi diagram

§ CV_EXPORTS_AS() [4/5]

cv::CV_EXPORTS_AS ( sumElems )

computes sum of array elements

§ CV_EXPORTS_AS() [5/5]

cv::CV_EXPORTS_AS ( randShuffle )

§ cvarrToMat()

Mat cv::cvarrToMat	(	const CvArr *	arr,
		bool	copyData = `false`,
		bool	allowND = `true`,
		int	coiMode = `0`
	)

converts array (CvMat or IplImage) to cv::Mat

§ cvtColor()

void cv::cvtColor	(	InputArray	src,
		OutputArray	dst,
		int	code,
		int	dstCn = `0`
	)

converts image from one color space to another

§ dct()

void cv::dct	(	InputArray	src,
		OutputArray	dst,
		int	flags = `0`
	)

performs forward or inverse 1D or 2D Discrete Cosine Transformation

§ decomposeProjectionMatrix()

void cv::decomposeProjectionMatrix	(	InputArray	projMatrix,
		OutputArray	cameraMatrix,
		OutputArray	rotMatrix,
		OutputArray	transVect,
		OutputArray	rotMatrixX = `noArray()`,
		OutputArray	rotMatrixY = `noArray()`,
		OutputArray	rotMatrixZ = `noArray()`,
		OutputArray	eulerAngles = `noArray()`
	)

Decomposes the projection matrix into camera matrix and the rotation martix and the translation vector.

§ destroyAllWindows()

void cv::destroyAllWindows ( )

§ destroyWindow()

void cv::destroyWindow ( const string & winname )

§ determinant()

double cv::determinant ( InputArray mtx )

computes determinant of a square matrix

§ dft()

void cv::dft	(	InputArray	src,
		OutputArray	dst,
		int	flags = `0`,
		int	nonzeroRows = `0`
	)

performs forward or inverse 1D or 2D Discrete Fourier Transformation

§ dilate()

void cv::dilate	(	InputArray	src,
		OutputArray	dst,
		InputArray	kernel,
		Point	anchor = `Point(-1,-1)`,
		int	iterations = `1`,
		int	borderType = `BORDER_CONSTANT`,
		const Scalar &	borderValue = `morphologyDefaultBorderValue()`
	)

dilates the image (applies the local maximum operator)

§ displayOverlay()

void cv::displayOverlay	(	const string &	winname,
		const string &	text,
		int delayms	CV_DEFAULT0
	)

§ displayStatusBar()

void cv::displayStatusBar	(	const string &	winname,
		const string &	text,
		int delayms	CV_DEFAULT0
	)

§ distanceTransform()

void cv::distanceTransform	(	InputArray	src,
		OutputArray	dst,
		int	distanceType,
		int	maskSize
	)

computes the distance transform map

§ divide() [1/2]

void cv::divide	(	InputArray	src1,
		InputArray	src2,
		OutputArray	dst,
		double	scale = `1`,
		int	dtype = `-1`
	)

computes element-wise weighted quotient of the two arrays (dst = scale*src1/src2)

§ divide() [2/2]

void cv::divide	(	double	scale,
		InputArray	src2,
		OutputArray	dst,
		int	dtype = `-1`
	)

computes element-wise weighted reciprocal of an array (dst = scale/src2)

§ dot()

template<typename _Tp >

DataType<_Tp>::work_type cv::dot	(	const Vector< _Tp > &	v1,
		const Vector< _Tp > &	v2
	)

inline

§ drawChessboardCorners()

void cv::drawChessboardCorners	(	InputOutputArray	image,
		Size	patternSize,
		InputArray	corners,
		bool	patternWasFound
	)

draws the checkerboard pattern (found or partly found) in the image

§ drawContours()

void cv::drawContours	(	InputOutputArray	image,
		InputArrayOfArrays	contours,
		int	contourIdx,
		const Scalar &	color,
		int	thickness = `1`,
		int	lineType = `8`,
		InputArray	hierarchy = `noArray()`,
		int	maxLevel = `INT_MAX`,
		Point	offset = `Point()`
	)

draws contours in the image

§ drawDataMatrixCodes()

void cv::drawDataMatrixCodes	(	InputOutputArray	image,
		const vector< string > &	codes,
		InputArray	corners
	)

§ drawKeypoints()

void cv::drawKeypoints	(	const Mat &	image,
		const vector< KeyPoint > &	keypoints,
		CV_OUT Mat &	outImage,
		const Scalar &	color = `Scalar::all(-1)`,
		int	flags = `DrawMatchesFlags::DEFAULT`
	)

§ drawMarker()

void cv::drawMarker	(	CV_IN_OUT Mat &	img,
		Point	position,
		const Scalar &	color,
		int	markerType = `MARKER_CROSS`,
		int	markerSize = `20`,
		int	thickness = `1`,
		int	line_type = `8`
	)

Draws a marker on a predefined position in an image.

The function drawMarker draws a marker on a given position in the image. For the moment several marker types are supported (MARKER_CROSS, MARKER_TILTED_CROSS, MARKER_STAR, MARKER_DIAMOND, MARKER_SQUARE, MARKER_TRIANGLE_UP and MARKER_TRIANGLE_DOWN).

Parameters

img	Image.
position	The point where the crosshair is positioned.
markerType	The specific type of marker you want to use, see
color	Line color.
thickness	Line thickness.
line_type	Type of the line, see cv::LineTypes
markerSize	The length of the marker axis [default = 20 pixels]

§ drawMatches() [1/2]

void cv::drawMatches	(	const Mat &	img1,
		const vector< KeyPoint > &	keypoints1,
		const Mat &	img2,
		const vector< KeyPoint > &	keypoints2,
		const vector< DMatch > &	matches1to2,
		Mat &	outImg,
		const Scalar &	matchColor = `Scalar::all(-1)`,
		const Scalar &	singlePointColor = `Scalar::all(-1)`,
		const vector< char > &	matchesMask = `vector< char >()`,
		int	flags = `DrawMatchesFlags::DEFAULT`
	)

§ drawMatches() [2/2]

void cv::drawMatches	(	const Mat &	img1,
		const vector< KeyPoint > &	keypoints1,
		const Mat &	img2,
		const vector< KeyPoint > &	keypoints2,
		const vector< vector< DMatch > > &	matches1to2,
		Mat &	outImg,
		const Scalar &	matchColor = `Scalar::all(-1)`,
		const Scalar &	singlePointColor = `Scalar::all(-1)`,
		const vector< vector< char > > &	matchesMask = `vector< vector< char > >()`,
		int	flags = `DrawMatchesFlags::DEFAULT`
	)

§ eigen() [1/3]

bool cv::eigen	(	InputArray	src,
		OutputArray	eigenvalues,
		int	lowindex = `-1`,
		int	highindex = `-1`
	)

finds eigenvalues of a symmetric matrix

§ eigen() [2/3]

bool cv::eigen	(	InputArray	src,
		OutputArray	eigenvalues,
		OutputArray	eigenvectors,
		int	lowindex = `-1`,
		int	highindex = `-1`
	)

finds eigenvalues and eigenvectors of a symmetric matrix

§ eigen() [3/3]

bool cv::eigen	(	InputArray	src,
		bool	computeEigenvectors,
		OutputArray	eigenvalues,
		OutputArray	eigenvectors
	)

§ eigen2cv()

template<typename _Tp , int _rows, int _cols, int _options, int _maxRows, int _maxCols>

void cv::eigen2cv	(	const Eigen::Matrix< _Tp, _rows, _cols, _options, _maxRows, _maxCols > &	src,
		Mat &	dst
	)

§ eigen2x2()

void cv::eigen2x2	(	const float *	a,
		float *	e,
		int	n
	)

§ ellipse() [1/2]

void cv::ellipse	(	CV_IN_OUT Mat &	img,
		Point	center,
		Size	axes,
		double	angle,
		double	startAngle,
		double	endAngle,
		const Scalar &	color,
		int	thickness = `1`,
		int	lineType = `8`,
		int	shift = `0`
	)

draws an elliptic arc, ellipse sector or a rotated ellipse in the image

§ ellipse() [2/2]

void cv::ellipse	(	CV_IN_OUT Mat &	img,
		const RotatedRect &	box,
		const Scalar &	color,
		int	thickness = `1`,
		int	lineType = `8`
	)

draws a rotated ellipse in the image

§ ellipse2Poly() [1/2]

void cv::ellipse2Poly	(	Point	center,
		Size	axes,
		int	angle,
		int	arcStart,
		int	arcEnd,
		int	delta,
		CV_OUT vector< Point > &	pts
	)

converts elliptic arc to a polygonal curve

§ ellipse2Poly() [2/2]

void cv::ellipse2Poly	(	Point2d	center,
		Size2d	axes,
		int	angle,
		int	arcStart,
		int	arcEnd,
		int	delta,
		CV_OUT vector< Point2d > &	pts
	)

§ EMD()

float cv::EMD	(	InputArray	signature1,
		InputArray	signature2,
		int	distType,
		InputArray	cost = `noArray()`,
		float *	lowerBound = `0`,
		OutputArray	flow = `noArray()`
	)

§ equalizeHist()

void cv::equalizeHist	(	InputArray	src,
		OutputArray	dst
	)

normalizes the grayscale image brightness and contrast by normalizing its histogram

§ erode()

void cv::erode	(	InputArray	src,
		OutputArray	dst,
		InputArray	kernel,
		Point	anchor = `Point(-1,-1)`,
		int	iterations = `1`,
		int	borderType = `BORDER_CONSTANT`,
		const Scalar &	borderValue = `morphologyDefaultBorderValue()`
	)

erodes the image (applies the local minimum operator)

§ error()

void cv::error ( const Exception & exc )

Signals an error and raises the exception.

By default the function prints information about the error to stderr, then it either stops if setBreakOnError() had been called before or raises the exception. It is possible to alternate error processing by using redirectError().

Parameters

exc	the exception raisen.

§ estimateAffine3D()

int cv::estimateAffine3D	(	InputArray	src,
		InputArray	dst,
		OutputArray	out,
		OutputArray	inliers,
		double	ransacThreshold = `3`,
		double	confidence = `0.99`
	)

§ estimateRigidTransform()

Mat cv::estimateRigidTransform	(	InputArray	src,
		InputArray	dst,
		bool	fullAffine
	)

estimates the best-fit Euqcidean, similarity, affine or perspective transformation

§ evaluateFeatureDetector()

void cv::evaluateFeatureDetector	(	const Mat &	img1,
		const Mat &	img2,
		const Mat &	H1to2,
		vector< KeyPoint > *	keypoints1,
		vector< KeyPoint > *	keypoints2,
		float &	repeatability,
		int &	correspCount,
		const Ptr< FeatureDetector > &	fdetector = `Ptr< FeatureDetector >()`
	)

§ evaluateGenericDescriptorMatcher()

void cv::evaluateGenericDescriptorMatcher	(	const Mat &	img1,
		const Mat &	img2,
		const Mat &	H1to2,
		vector< KeyPoint > &	keypoints1,
		vector< KeyPoint > &	keypoints2,
		vector< vector< DMatch > > *	matches1to2,
		vector< vector< uchar > > *	correctMatches1to2Mask,
		vector< Point2f > &	recallPrecisionCurve,
		const Ptr< GenericDescriptorMatcher > &	dmatch = `Ptr< GenericDescriptorMatcher >()`
	)

§ exp() [1/2]

void cv::exp	(	InputArray	src,
		OutputArray	dst
	)

computes exponent of each matrix element (dst = e**src)

§ exp() [2/2]

void cv::exp	(	const float *	src,
		float *	dst,
		int	n
	)

§ extractChannel()

void cv::extractChannel	(	InputArray	src,
		OutputArray	dst,
		int	coi
	)

extracts a single channel from src (coi is 0-based index)

§ extractImageCOI()

void cv::extractImageCOI	(	const CvArr *	arr,
		OutputArray	coiimg,
		int	coi = `-1`
	)

extracts Channel of Interest from CvMat or IplImage and makes cv::Mat out of it.

§ FAST()

void cv::FAST	(	InputArray	image,
		CV_OUT vector< KeyPoint > &	keypoints,
		int	threshold,
		bool	nonmaxSuppression = `true`
	)

computes the angle in degrees (0..360) of the vector (x,y)

§ fastAtan2() [2/2]

void cv::fastAtan2	(	const float *	y,
		const float *	x,
		float *	dst,
		int	n,
		bool	angleInDegrees
	)

§ fastFree()

void cv::fastFree ( void * ptr )

Frees the memory allocated with cv::fastMalloc

This is the corresponding deallocation function for cv::fastMalloc(). When ptr==NULL, the function has no effect.

§ fastMalloc()

void* cv::fastMalloc ( size_t bufSize )

Allocates memory buffer

This is specialized OpenCV memory allocation function that returns properly aligned memory buffers. The usage is identical to malloc(). The allocated buffers must be freed with cv::fastFree(). If there is not enough memory, the function calls cv::error(), which raises an exception.

Parameters

bufSize buffer size in bytes

Returns: the allocated memory buffer.

§ fastNlMeansDenoising()

void cv::fastNlMeansDenoising	(	InputArray	src,
		OutputArray	dst,
		float	h = `3`,
		int	templateWindowSize = `7`,
		int	searchWindowSize = `21`
	)

§ fastNlMeansDenoisingColored()

void cv::fastNlMeansDenoisingColored	(	InputArray	src,
		OutputArray	dst,
		float	h = `3`,
		float	hColor = `3`,
		int	templateWindowSize = `7`,
		int	searchWindowSize = `21`
	)

§ fastNlMeansDenoisingColoredMulti()

void cv::fastNlMeansDenoisingColoredMulti	(	InputArrayOfArrays	srcImgs,
		OutputArray	dst,
		int	imgToDenoiseIndex,
		int	temporalWindowSize,
		float	h = `3`,
		float	hColor = `3`,
		int	templateWindowSize = `7`,
		int	searchWindowSize = `21`
	)

§ fastNlMeansDenoisingMulti()

void cv::fastNlMeansDenoisingMulti	(	InputArrayOfArrays	srcImgs,
		OutputArray	dst,
		int	imgToDenoiseIndex,
		int	temporalWindowSize,
		float	h = `3`,
		int	templateWindowSize = `7`,
		int	searchWindowSize = `21`
	)

§ FASTX()

void cv::FASTX	(	InputArray	image,
		CV_OUT vector< KeyPoint > &	keypoints,
		int	threshold,
		bool	nonmaxSuppression,
		int	type
	)

§ fillConvexPoly() [1/2]

void cv::fillConvexPoly	(	Mat &	img,
		const Point *	pts,
		int	npts,
		const Scalar &	color,
		int	lineType = `8`,
		int	shift = `0`
	)

draws a filled convex polygon in the image

§ fillConvexPoly() [2/2]

void cv::fillConvexPoly	(	InputOutputArray	img,
		InputArray	points,
		const Scalar &	color,
		int	lineType = `8`,
		int	shift = `0`
	)

§ fillPoly() [1/2]

void cv::fillPoly	(	Mat &	img,
		const Point **	pts,
		const int *	npts,
		int	ncontours,
		const Scalar &	color,
		int	lineType = `8`,
		int	shift = `0`,
		Point	offset = `Point()`
	)

fills an area bounded by one or more polygons

§ fillPoly() [2/2]

void cv::fillPoly	(	InputOutputArray	img,
		InputArrayOfArrays	pts,
		const Scalar &	color,
		int	lineType = `8`,
		int	shift = `0`,
		Point	offset = `Point()`
	)

§ filter2D()

void cv::filter2D	(	InputArray	src,
		OutputArray	dst,
		int	ddepth,
		InputArray	kernel,
		Point	anchor = `Point(-1,-1)`,
		double	delta = `0`,
		int	borderType = `BORDER_DEFAULT`
	)

applies non-separable 2D linear filter to the image

§ filterSpeckles()

void cv::filterSpeckles	(	InputOutputArray	img,
		double	newVal,
		int	maxSpeckleSize,
		double	maxDiff,
		InputOutputArray	buf = `noArray()`
	)

filters off speckles (small regions of incorrectly computed disparity)

§ find4QuadCornerSubpix()

bool cv::find4QuadCornerSubpix	(	InputArray	img,
		InputOutputArray	corners,
		Size	region_size
	)

finds subpixel-accurate positions of the chessboard corners

§ findChessboardCorners()

bool cv::findChessboardCorners	(	InputArray	image,
		Size	patternSize,
		OutputArray	corners,
		int	flags = `CALIB_CB_ADAPTIVE_THRESH+CALIB_CB_NORMALIZE_IMAGE`
	)

finds checkerboard pattern of the specified size in the image

§ findCirclesGrid()

bool cv::findCirclesGrid	(	InputArray	image,
		Size	patternSize,
		OutputArray	centers,
		int	flags = `CALIB_CB_SYMMETRIC_GRID`,
		const Ptr< FeatureDetector > &	blobDetector = `new SimpleBlobDetector()`
	)

finds circles' grid pattern of the specified size in the image

§ findCirclesGridDefault()

bool cv::findCirclesGridDefault	(	InputArray	image,
		Size	patternSize,
		OutputArray	centers,
		int	flags = `CALIB_CB_SYMMETRIC_GRID`
	)

the deprecated function. Use findCirclesGrid() instead of it.

§ findContours() [1/2]

void cv::findContours	(	InputOutputArray	image,
		OutputArrayOfArrays	contours,
		OutputArray	hierarchy,
		int	mode,
		int	method,
		Point	offset = `Point()`
	)

retrieves contours and the hierarchical information from black-n-white image.

§ findContours() [2/2]

void cv::findContours	(	InputOutputArray	image,
		OutputArrayOfArrays	contours,
		int	mode,
		int	method,
		Point	offset = `Point()`
	)

retrieves contours from black-n-white image.

§ findDataMatrix()

void cv::findDataMatrix	(	InputArray	image,
		CV_OUT vector< string > &	codes,
		OutputArray	corners = `noArray()`,
		OutputArrayOfArrays	dmtx = `noArray()`
	)

§ findFundamentalMat() [1/2]

Mat cv::findFundamentalMat	(	InputArray	points1,
		InputArray	points2,
		int	method = `FM_RANSAC`,
		double	param1 = `3.`,
		double	param2 = `0.99`,
		OutputArray	mask = `noArray()`
	)

finds fundamental matrix from a set of corresponding 2D points

§ findFundamentalMat() [2/2]

Mat cv::findFundamentalMat	(	InputArray	points1,
		InputArray	points2,
		OutputArray	mask,
		int	method = `FM_RANSAC`,
		double	param1 = `3.`,
		double	param2 = `0.99`
	)

variant of findFundamentalMat for backward compatibility

§ findHomography() [1/2]

Mat cv::findHomography	(	InputArray	srcPoints,
		InputArray	dstPoints,
		int	method = `0`,
		double	ransacReprojThreshold = `3`,
		OutputArray	mask = `noArray()`
	)

computes the best-fit perspective transformation mapping srcPoints to dstPoints.

§ findHomography() [2/2]

Mat cv::findHomography	(	InputArray	srcPoints,
		InputArray	dstPoints,
		OutputArray	mask,
		int	method = `0`,
		double	ransacReprojThreshold = `3`
	)

variant of findHomography for backward compatibility

§ findNonZero()

void cv::findNonZero	(	InputArray	src,
		OutputArray	idx
	)

returns the list of locations of non-zero pixels

§ fitEllipse()

RotatedRect cv::fitEllipse ( InputArray points )

fits ellipse to the set of 2D points

§ fitLine()

void cv::fitLine	(	InputArray	points,
		OutputArray	line,
		int	distType,
		double	param,
		double	reps,
		double	aeps
	)

fits line to the set of 2D points using M-estimator algorithm

§ flip()

void cv::flip	(	InputArray	src,
		OutputArray	dst,
		int	flipCode
	)

reverses the order of the rows, columns or both in a matrix

§ floodFill() [1/2]

int cv::floodFill	(	InputOutputArray	image,
		Point	seedPoint,
		Scalar	newVal,
		CV_OUT Rect *	rect = `0`,
		Scalar	loDiff = `Scalar()`,
		Scalar	upDiff = `Scalar()`,
		int	flags = `4`
	)

fills the semi-uniform image region starting from the specified seed point

§ floodFill() [2/2]

int cv::floodFill	(	InputOutputArray	image,
		InputOutputArray	mask,
		Point	seedPoint,
		Scalar	newVal,
		CV_OUT Rect *	rect = `0`,
		Scalar	loDiff = `Scalar()`,
		Scalar	upDiff = `Scalar()`,
		int	flags = `4`
	)

fills the semi-uniform image region and/or the mask starting from the specified seed point

§ fontQt()

CvFont cv::fontQt	(	const string &	nameFont,
		int	pointSize = `-1`,
		Scalar	color = `Scalar::all(0)`,
		int	weight = `CV_FONT_NORMAL`,
		int	style = `CV_STYLE_NORMAL`,
		int	spacing = `0`
	)

§ format()

string cv::format	(	const char *	fmt,
			...
	)

§ fromUtf16()

string cv::fromUtf16 ( const WString & str )

§ GaussianBlur()

void cv::GaussianBlur	(	InputArray	src,
		OutputArray	dst,
		Size	ksize,
		double	sigmaX,
		double	sigmaY = `0`,
		int	borderType = `BORDER_DEFAULT`
	)

smooths the image using Gaussian filter.

§ gemm()

void cv::gemm	(	InputArray	src1,
		InputArray	src2,
		double	alpha,
		InputArray	src3,
		double	beta,
		OutputArray	dst,
		int	flags = `0`
	)

implements generalized matrix product algorithm GEMM from BLAS

§ generateColors()

void cv::generateColors	(	std::vector< Scalar > &	colors,
		size_t	count,
		size_t	factor = `100`
	)

§ getAffineTransform() [1/2]

Mat cv::getAffineTransform	(	const Point2f	src[],
		const Point2f	dst[]
	)

returns 2x3 affine transformation for the corresponding 3 point pairs.

§ getAffineTransform() [2/2]

Mat cv::getAffineTransform	(	InputArray	src,
		InputArray	dst
	)

§ getBuildInformation()

const string& cv::getBuildInformation ( )

§ getColumnSumFilter()

Ptr<BaseColumnFilter> cv::getColumnSumFilter	(	int	sumType,
		int	dstType,
		int	ksize,
		int	anchor = `-1`,
		double	scale = `1`
	)

returns vertical 1D box filter

§ getConvertElem()

ConvertData cv::getConvertElem	(	int	fromType,
		int	toType
	)

returns the function for converting pixels from one data type to another

§ getConvertFunc()

BinaryFunc cv::getConvertFunc	(	int	sdepth,
		int	ddepth
	)

§ getConvertScaleElem()

ConvertScaleData cv::getConvertScaleElem	(	int	fromType,
		int	toType
	)

returns the function for converting pixels from one data type to another with the optional scaling

§ getConvertScaleFunc()

BinaryFunc cv::getConvertScaleFunc	(	int	sdepth,
		int	ddepth
	)

§ getCopyMaskFunc()

BinaryFunc cv::getCopyMaskFunc ( size_t esz )

§ getCPUTickCount()

int64 cv::getCPUTickCount ( )

Returns the number of CPU ticks.

On platforms where the feature is available, the function returns the number of CPU ticks since the certain event (normally, the system power-on moment). Using this function one can accurately measure the execution time of very small code fragments, for which cv::getTickCount() granularity is not enough.

§ getData()

uchar* cv::getData ( IplImage * image )

inline

§ getDefaultNewCameraMatrix()

Mat cv::getDefaultNewCameraMatrix	(	InputArray	cameraMatrix,
		Size	imgsize = `Size()`,
		bool	centerPrincipalPoint = `false`
	)

returns the default new camera matrix (by default it is the same as cameraMatrix unless centerPricipalPoint=true)

§ getDerivKernels()

void cv::getDerivKernels	(	OutputArray	kx,
		OutputArray	ky,
		int	dx,
		int	dy,
		int	ksize,
		bool	normalize = `false`,
		int	ktype = `CV_32F`
	)

initializes kernels of the generalized Sobel operator

§ getGaborKernel()

Mat cv::getGaborKernel	(	Size	ksize,
		double	sigma,
		double	theta,
		double	lambd,
		double	gamma,
		double	psi = `CV_PI *0.5`,
		int	ktype = `CV_64F`
	)

returns the Gabor kernel with the specified parameters

§ getGaussianKernel()

Mat cv::getGaussianKernel	(	int	ksize,
		double	sigma,
		int	ktype = `CV_64F`
	)

returns the Gaussian kernel with the specified parameters

§ getKernelType()

int cv::getKernelType	(	InputArray	kernel,
		Point	anchor
	)

returns type (one of KERNEL_*) of 1D or 2D kernel specified by its coefficients.

§ getLinearColumnFilter()

Ptr<BaseColumnFilter> cv::getLinearColumnFilter	(	int	bufType,
		int	dstType,
		InputArray	kernel,
		int	anchor,
		int	symmetryType,
		double	delta = `0`,
		int	bits = `0`
	)

returns the primitive column filter with the specified kernel

§ getLinearFilter()

Ptr<BaseFilter> cv::getLinearFilter	(	int	srcType,
		int	dstType,
		InputArray	kernel,
		Point	anchor = `Point(-1,-1)`,
		double	delta = `0`,
		int	bits = `0`
	)

returns 2D filter with the specified kernel

§ getLinearRowFilter()

Ptr<BaseRowFilter> cv::getLinearRowFilter	(	int	srcType,
		int	bufType,
		InputArray	kernel,
		int	anchor,
		int	symmetryType
	)

returns the primitive row filter with the specified kernel

§ getMorphologyColumnFilter()

Ptr<BaseColumnFilter> cv::getMorphologyColumnFilter	(	int	op,
		int	type,
		int	ksize,
		int	anchor = `-1`
	)

returns vertical 1D morphological filter

§ getMorphologyFilter()

Ptr<BaseFilter> cv::getMorphologyFilter	(	int	op,
		int	type,
		InputArray	kernel,
		Point	anchor = `Point(-1,-1)`
	)

returns 2D morphological filter

§ getMorphologyRowFilter()

Ptr<BaseRowFilter> cv::getMorphologyRowFilter	(	int	op,
		int	type,
		int	ksize,
		int	anchor = `-1`
	)

returns horizontal 1D morphological filter

§ getNearestPoint()

int cv::getNearestPoint	(	const vector< Point2f > &	recallPrecisionCurve,
		float	l_precision
	)

§ getNumberOfCPUs()

int cv::getNumberOfCPUs ( )

returns the number of CPUs (including hyper-threading)

§ getNumThreads()

int cv::getNumThreads ( )

§ getOptimalDFTSize()

int cv::getOptimalDFTSize ( int vecsize )

computes the minimal vector size vecsize1 >= vecsize so that the dft() of the vector of length vecsize1 can be computed efficiently

§ getOptimalNewCameraMatrix()

Mat cv::getOptimalNewCameraMatrix	(	InputArray	cameraMatrix,
		InputArray	distCoeffs,
		Size	imageSize,
		double	alpha,
		Size	newImgSize = `Size()`,
		CV_OUT Rect *	validPixROI = `0`,
		bool	centerPrincipalPoint = `false`
	)

returns the optimal new camera matrix

§ getPerspectiveTransform() [1/2]

Mat cv::getPerspectiveTransform	(	const Point2f	src[],
		const Point2f	dst[]
	)

returns 3x3 perspective transformation for the corresponding 4 point pairs.

§ getPerspectiveTransform() [2/2]

Mat cv::getPerspectiveTransform	(	InputArray	src,
		InputArray	dst
	)

§ getRecall()

float cv::getRecall	(	const vector< Point2f > &	recallPrecisionCurve,
		float	l_precision
	)

§ getRectSubPix()

void cv::getRectSubPix	(	InputArray	image,
		Size	patchSize,
		Point2f	center,
		OutputArray	patch,
		int	patchType = `-1`
	)

extracts rectangle from the image at sub-pixel location

§ getRotationMatrix2D()

Mat cv::getRotationMatrix2D	(	Point2f	center,
		double	angle,
		double	scale
	)

returns 2x3 affine transformation matrix for the planar rotation.

§ getRowSumFilter()

Ptr<BaseRowFilter> cv::getRowSumFilter	(	int	srcType,
		int	sumType,
		int	ksize,
		int	anchor = `-1`
	)

returns horizontal 1D box filter

§ getSeqElem()

schar* cv::getSeqElem	(	const CvSeq *	seq,
		int	index
	)

§ getStructuringElement()

Mat cv::getStructuringElement	(	int	shape,
		Size	ksize,
		Point	anchor = `Point(-1,-1)`
	)

returns structuring element of the specified shape and size

§ getTextSize()

Size cv::getTextSize	(	const string &	text,
		int	fontFace,
		double	fontScale,
		int	thickness,
		CV_OUT int *	baseLine
	)

returns bounding box of the text string

§ getThreadNum()

int cv::getThreadNum ( )

§ getTickCount()

int64 cv::getTickCount ( )

Returns the number of ticks.

The function returns the number of ticks since the certain event (e.g. when the machine was turned on). It can be used to initialize cv::RNG or to measure a function execution time by reading the tick count before and after the function call. The granularity of ticks depends on the hardware and OS used. Use cv::getTickFrequency() to convert ticks to seconds.

§ getTickFrequency()

double cv::getTickFrequency ( )

Returns the number of ticks per seconds.

The function returns the number of ticks (as returned by cv::getTickCount()) per second. The following code computes the execution time in milliseconds:

double exec_time = (double)getTickCount();
// do something ...
exec_time = ((double)getTickCount() - exec_time)*1000./getTickFrequency();

§ getTrackbarPos()

int cv::getTrackbarPos	(	const string &	trackbarname,
		const string &	winname
	)

§ getValidDisparityROI()

Rect cv::getValidDisparityROI	(	Rect	roi1,
		Rect	roi2,
		int	minDisparity,
		int	numberOfDisparities,
		int	SADWindowSize
	)

computes valid disparity ROI from the valid ROIs of the rectified images (that are returned by cv::stereoRectify())

§ getWindowProperty()

double cv::getWindowProperty	(	const string &	winname,
		int	prop_id
	)

§ glob()

void cv::glob	(	String	pattern,
		std::vector< String > &	result,
		bool	recursive = `false`
	)

§ goodFeaturesToTrack()

void cv::goodFeaturesToTrack	(	InputArray	image,
		OutputArray	corners,
		int	maxCorners,
		double	qualityLevel,
		double	minDistance,
		InputArray	mask = `noArray()`,
		int	blockSize = `3`,
		bool	useHarrisDetector = `false`,
		double	k = `0.04`
	)

finds the strong enough corners where the cornerMinEigenVal() or cornerHarris() report the local maxima

§ grabCut()

void cv::grabCut	(	InputArray	img,
		InputOutputArray	mask,
		Rect	rect,
		InputOutputArray	bgdModel,
		InputOutputArray	fgdModel,
		int	iterCount,
		int	mode = `GC_EVAL`
	)

segments the image using GrabCut algorithm

§ groupRectangles() [1/4]

void cv::groupRectangles	(	CV_OUT CV_IN_OUT vector< Rect > &	rectList,
		int	groupThreshold,
		double	eps = `0.2`
	)

§ groupRectangles() [2/4]

void cv::groupRectangles	(	CV_OUT CV_IN_OUT vector< Rect > &	rectList,
		CV_OUT vector< int > &	weights,
		int	groupThreshold,
		double	eps = `0.2`
	)

§ groupRectangles() [3/4]

void cv::groupRectangles	(	vector< Rect > &	rectList,
		int	groupThreshold,
		double	eps,
		vector< int > *	weights,
		vector< double > *	levelWeights
	)

§ groupRectangles() [4/4]

void cv::groupRectangles	(	vector< Rect > &	rectList,
		vector< int > &	rejectLevels,
		vector< double > &	levelWeights,
		int	groupThreshold,
		double	eps = `0.2`
	)

§ groupRectangles_meanshift()

void cv::groupRectangles_meanshift	(	vector< Rect > &	rectList,
		vector< double > &	foundWeights,
		vector< double > &	foundScales,
		double	detectThreshold = `0.0`,
		Size	winDetSize = `Size(64, 128)`
	)

§ hconcat() [1/3]

void cv::hconcat	(	const Mat *	src,
		size_t	nsrc,
		OutputArray	dst
	)

§ hconcat() [2/3]

void cv::hconcat	(	InputArray	src1,
		InputArray	src2,
		OutputArray	dst
	)

§ hconcat() [3/3]

void cv::hconcat	(	InputArrayOfArrays	src,
		OutputArray	dst
	)

§ HoughCircles()

void cv::HoughCircles	(	InputArray	image,
		OutputArray	circles,
		int	method,
		double	dp,
		double	minDist,
		double	param1 = `100`,
		double	param2 = `100`,
		int	minRadius = `0`,
		int	maxRadius = `0`
	)

finds circles in the grayscale image using 2+1 gradient Hough transform

§ HoughLines()

void cv::HoughLines	(	InputArray	image,
		OutputArray	lines,
		double	rho,
		double	theta,
		int	threshold,
		double	srn = `0`,
		double	stn = `0`
	)

finds lines in the black-n-white image using the standard or pyramid Hough transform

§ HoughLinesP()

void cv::HoughLinesP	(	InputArray	image,
		OutputArray	lines,
		double	rho,
		double	theta,
		int	threshold,
		double	minLineLength = `0`,
		double	maxLineGap = `0`
	)

finds line segments in the black-n-white image using probabilistic Hough transform

§ HuMoments() [1/2]

void cv::HuMoments	(	const Moments &	moments,
		double	hu[7]
	)

computes 7 Hu invariants from the moments

§ HuMoments() [2/2]

void cv::HuMoments	(	const Moments &	m,
		CV_OUT OutputArray	hu
	)

§ idct()

void cv::idct	(	InputArray	src,
		OutputArray	dst,
		int	flags = `0`
	)

performs inverse 1D or 2D Discrete Cosine Transformation

§ idft()

void cv::idft	(	InputArray	src,
		OutputArray	dst,
		int	flags = `0`,
		int	nonzeroRows = `0`
	)

performs inverse 1D or 2D Discrete Fourier Transformation

§ imdecode() [1/2]

Mat cv::imdecode	(	InputArray	buf,
		int	flags
	)

§ imdecode() [2/2]

Mat cv::imdecode	(	InputArray	buf,
		int	flags,
		Mat *	dst
	)

§ imencode()

bool cv::imencode	(	const string &	ext,
		InputArray	img,
		CV_OUT vector< uchar > &	buf,
		const vector< int > &	params = `vector< int >()`
	)

§ imread()

Mat cv::imread	(	const string &	filename,
		int	flags = `1`
	)

§ imshow()

void cv::imshow	(	const string &	winname,
		InputArray	mat
	)

§ imwrite()

bool cv::imwrite	(	const string &	filename,
		InputArray	img,
		const vector< int > &	params = `vector< int >()`
	)

§ initCameraMatrix2D()

Mat cv::initCameraMatrix2D	(	InputArrayOfArrays	objectPoints,
		InputArrayOfArrays	imagePoints,
		Size	imageSize,
		double	aspectRatio = `1.`
	)

initializes camera matrix from a few 3D points and the corresponding projections.

§ initModule_contrib()

bool cv::initModule_contrib ( )

§ initModule_features2d()

bool cv::initModule_features2d ( )

§ initModule_ml()

bool cv::initModule_ml ( void )

§ initModule_nonfree()

bool cv::initModule_nonfree ( )

§ initModule_video()

bool cv::initModule_video ( void )

§ initUndistortRectifyMap()

void cv::initUndistortRectifyMap	(	InputArray	cameraMatrix,
		InputArray	distCoeffs,
		InputArray	R,
		InputArray	newCameraMatrix,
		Size	size,
		int	m1type,
		OutputArray	map1,
		OutputArray	map2
	)

initializes maps for cv::remap() to correct lens distortion and optionally rectify the image

§ initWideAngleProjMap()

float cv::initWideAngleProjMap	(	InputArray	cameraMatrix,
		InputArray	distCoeffs,
		Size	imageSize,
		int	destImageWidth,
		int	m1type,
		OutputArray	map1,
		OutputArray	map2,
		int	projType = `PROJ_SPHERICAL_EQRECT`,
		double	alpha = `0`
	)

initializes maps for cv::remap() for wide-angle

§ inpaint()

void cv::inpaint	(	InputArray	src,
		InputArray	inpaintMask,
		OutputArray	dst,
		double	inpaintRadius,
		int	flags
	)

restores the damaged image areas using one of the available intpainting algorithms

§ inRange()

void cv::inRange	(	InputArray	src,
		InputArray	lowerb,
		InputArray	upperb,
		OutputArray	dst
	)

set mask elements for those array elements which are within the element-specific bounding box (dst = lowerb <= src && src < upperb)

§ insertChannel()

void cv::insertChannel	(	InputArray	src,
		InputOutputArray	dst,
		int	coi
	)

inserts a single channel to dst (coi is 0-based index)

§ insertImageCOI()

void cv::insertImageCOI	(	InputArray	coiimg,
		CvArr *	arr,
		int	coi = `-1`
	)

inserts single-channel cv::Mat into a multi-channel CvMat or IplImage

§ integral()

void cv::integral	(	InputArray	src,
		OutputArray	sum,
		int	sdepth = `-1`
	)

computes the integral image

§ intersectConvexConvex()

float cv::intersectConvexConvex	(	InputArray	_p1,
		InputArray	_p2,
		OutputArray	_p12,
		bool	handleNested = `true`
	)

finds intersection of two convex polygons

§ invert()

double cv::invert	(	InputArray	src,
		OutputArray	dst,
		int	flags = `DECOMP_LU`
	)

computes inverse or pseudo-inverse matrix

§ invertAffineTransform()

void cv::invertAffineTransform	(	InputArray	M,
		OutputArray	iM
	)

computes 2x3 affine transformation matrix that is inverse to the specified 2x3 affine transformation.

§ isContourConvex()

bool cv::isContourConvex ( InputArray contour )

returns true if the contour is convex. Does not support contours with self-intersection

§ kmeans()

double cv::kmeans	(	InputArray	data,
		int	K,
		CV_OUT InputOutputArray	bestLabels,
		TermCriteria	criteria,
		int	attempts,
		int	flags,
		OutputArray	centers = `noArray()`
	)

clusters the input data using k-Means algorithm

§ Laplacian()

void cv::Laplacian	(	InputArray	src,
		OutputArray	dst,
		int	ddepth,
		int	ksize = `1`,
		double	scale = `1`,
		double	delta = `0`,
		int	borderType = `BORDER_DEFAULT`
	)

applies Laplacian operator to the image

§ line()

void cv::line	(	CV_IN_OUT Mat &	img,
		Point	pt1,
		Point	pt2,
		const Scalar &	color,
		int	thickness = `1`,
		int	lineType = `8`,
		int	shift = `0`
	)

draws the line segment (pt1, pt2) in the image

§ loadWindowParameters()

void cv::loadWindowParameters ( const string & windowName )

§ log() [1/2]

void cv::log	(	InputArray	src,
		OutputArray	dst
	)

computes natural logarithm of absolute value of each matrix element: dst = log(abs(src))

§ log() [2/2]

void cv::log	(	const float *	src,
		float *	dst,
		int	n
	)

§ LU() [1/2]

int cv::LU	(	float *	A,
		size_t	astep,
		int	m,
		float *	b,
		size_t	bstep,
		int	n
	)

§ LU() [2/2]

int cv::LU	(	double *	A,
		size_t	astep,
		int	m,
		double *	b,
		size_t	bstep,
		int	n
	)

§ LUT()

void cv::LUT	(	InputArray	src,
		InputArray	lut,
		OutputArray	dst,
		int	interpolation = `0`
	)

transforms array of numbers using a lookup table: dst(i)=lut(src(i))

§ magnitude() [1/2]

void cv::magnitude	(	const float *	x,
		const float *	y,
		float *	dst,
		int	n
	)

§ magnitude() [2/2]

void cv::magnitude	(	InputArray	x,
		InputArray	y,
		OutputArray	magnitude
	)

computes magnitude (magnitude(i)) of each (x(i), y(i)) vector

§ Mahalanobis()

double cv::Mahalanobis	(	InputArray	v1,
		InputArray	v2,
		InputArray	icovar
	)

computes Mahalanobis distance between two vectors: sqrt((v1-v2)'icovar(v1-v2)), where icovar is the inverse covariation matrix

§ Mahalonobis()

double cv::Mahalonobis	(	InputArray	v1,
		InputArray	v2,
		InputArray	icovar
	)

a synonym for Mahalanobis

§ makePtr() [1/11]

template<typename T >

Ptr< T > cv::makePtr ( )

§ makePtr() [2/11]

template<typename T , typename A1 >

Ptr< T > cv::makePtr ( const A1 & a1 )

§ makePtr() [3/11]

template<typename T , typename A1 , typename A2 >

Ptr< T > cv::makePtr	(	const A1 &	a1,
		const A2 &	a2
	)

§ makePtr() [4/11]

template<typename T , typename A1 , typename A2 , typename A3 >

Ptr< T > cv::makePtr	(	const A1 &	a1,
		const A2 &	a2,
		const A3 &	a3
	)

§ makePtr() [5/11]

template<typename T , typename A1 , typename A2 , typename A3 , typename A4 >

Ptr< T > cv::makePtr	(	const A1 &	a1,
		const A2 &	a2,
		const A3 &	a3,
		const A4 &	a4
	)

§ makePtr() [6/11]

template<typename T , typename A1 , typename A2 , typename A3 , typename A4 , typename A5 >

Ptr< T > cv::makePtr	(	const A1 &	a1,
		const A2 &	a2,
		const A3 &	a3,
		const A4 &	a4,
		const A5 &	a5
	)

§ makePtr() [7/11]

template<typename T , typename A1 , typename A2 , typename A3 , typename A4 , typename A5 , typename A6 >

Ptr< T > cv::makePtr	(	const A1 &	a1,
		const A2 &	a2,
		const A3 &	a3,
		const A4 &	a4,
		const A5 &	a5,
		const A6 &	a6
	)

§ makePtr() [8/11]

template<typename T , typename A1 , typename A2 , typename A3 , typename A4 , typename A5 , typename A6 , typename A7 >

Ptr< T > cv::makePtr	(	const A1 &	a1,
		const A2 &	a2,
		const A3 &	a3,
		const A4 &	a4,
		const A5 &	a5,
		const A6 &	a6,
		const A7 &	a7
	)

§ makePtr() [9/11]

template<typename T , typename A1 , typename A2 , typename A3 , typename A4 , typename A5 , typename A6 , typename A7 , typename A8 >

Ptr< T > cv::makePtr	(	const A1 &	a1,
		const A2 &	a2,
		const A3 &	a3,
		const A4 &	a4,
		const A5 &	a5,
		const A6 &	a6,
		const A7 &	a7,
		const A8 &	a8
	)

§ makePtr() [10/11]

template<typename T , typename A1 , typename A2 , typename A3 , typename A4 , typename A5 , typename A6 , typename A7 , typename A8 , typename A9 >

Ptr< T > cv::makePtr	(	const A1 &	a1,
		const A2 &	a2,
		const A3 &	a3,
		const A4 &	a4,
		const A5 &	a5,
		const A6 &	a6,
		const A7 &	a7,
		const A8 &	a8,
		const A9 &	a9
	)

§ makePtr() [11/11]

template<typename T , typename A1 , typename A2 , typename A3 , typename A4 , typename A5 , typename A6 , typename A7 , typename A8 , typename A9 , typename A10 >

Ptr< T > cv::makePtr	(	const A1 &	a1,
		const A2 &	a2,
		const A3 &	a3,
		const A4 &	a4,
		const A5 &	a5,
		const A6 &	a6,
		const A7 &	a7,
		const A8 &	a8,
		const A9 &	a9,
		const A10 &	a10
	)

§ matchShapes()

double cv::matchShapes	(	InputArray	contour1,
		InputArray	contour2,
		int	method,
		double	parameter
	)

matches two contours using one of the available algorithms

§ matchTemplate()

void cv::matchTemplate	(	InputArray	image,
		InputArray	templ,
		OutputArray	result,
		int	method
	)

computes the proximity map for the raster template and the image where the template is searched for

§ matMulDeriv()

void cv::matMulDeriv	(	InputArray	A,
		InputArray	B,
		OutputArray	dABdA,
		OutputArray	dABdB
	)

computes derivatives of the matrix product w.r.t each of the multiplied matrix coefficients

§ max() [1/6]

MatExpr cv::max	(	const Mat &	a,
		const Mat &	b
	)

§ max() [2/6]

MatExpr cv::max	(	const Mat &	a,
		double	s
	)

§ max() [3/6]

MatExpr cv::max	(	double	s,
		const Mat &	a
	)

§ max() [4/6]

void cv::max	(	InputArray	src1,
		InputArray	src2,
		OutputArray	dst
	)

computes per-element maximum of two arrays (dst = max(src1, src2))

§ max() [5/6]

void cv::max	(	const Mat &	src1,
		const Mat &	src2,
		Mat &	dst
	)

computes per-element maximum of two arrays (dst = max(src1, src2))

§ max() [6/6]

void cv::max	(	const Mat &	src1,
		double	src2,
		Mat &	dst
	)

computes per-element maximum of array and scalar (dst = max(src1, src2))

§ mean()

Scalar cv::mean	(	InputArray	src,
		InputArray	mask = `noArray()`
	)

computes mean value of selected array elements

§ meanShift()

int cv::meanShift	(	InputArray	probImage,
		CV_OUT CV_IN_OUT Rect &	window,
		TermCriteria	criteria
	)

updates the object tracking window using meanshift algorithm

§ meanStdDev()

void cv::meanStdDev	(	InputArray	src,
		OutputArray	mean,
		OutputArray	stddev,
		InputArray	mask = `noArray()`
	)

computes mean value and standard deviation of all or selected array elements

§ medianBlur()

void cv::medianBlur	(	InputArray	src,
		OutputArray	dst,
		int	ksize
	)

smooths the image using median filter.

§ merge() [1/3]

void cv::merge	(	const Mat *	mv,
		size_t	count,
		OutputArray	dst
	)

makes multi-channel array out of several single-channel arrays

§ merge() [2/3]

void cv::merge	(	const vector< Mat > &	mv,
		OutputArray	dst
	)

§ merge() [3/3]

void cv::merge	(	InputArrayOfArrays	mv,
		OutputArray	dst
	)

makes multi-channel array out of several single-channel arrays

§ min() [1/6]

MatExpr cv::min	(	const Mat &	a,
		const Mat &	b
	)

§ min() [2/6]

MatExpr cv::min	(	const Mat &	a,
		double	s
	)

§ min() [3/6]

MatExpr cv::min	(	double	s,
		const Mat &	a
	)

§ min() [4/6]

void cv::min	(	InputArray	src1,
		InputArray	src2,
		OutputArray	dst
	)

computes per-element minimum of two arrays (dst = min(src1, src2))

§ min() [5/6]

void cv::min	(	const Mat &	src1,
		const Mat &	src2,
		Mat &	dst
	)

computes per-element minimum of two arrays (dst = min(src1, src2))

§ min() [6/6]

void cv::min	(	const Mat &	src1,
		double	src2,
		Mat &	dst
	)

computes per-element minimum of array and scalar (dst = min(src1, src2))

§ minAreaRect()

RotatedRect cv::minAreaRect ( InputArray points )

computes the minimal rotated rectangle for a set of points

§ minEnclosingCircle()

void cv::minEnclosingCircle	(	InputArray	points,
		CV_OUT Point2f &	center,
		CV_OUT float &	radius
	)

computes the minimal enclosing circle for a set of points

§ minMaxIdx()

void cv::minMaxIdx	(	InputArray	src,
		double *	minVal,
		double *	maxVal,
		int *	minIdx = `0`,
		int *	maxIdx = `0`,
		InputArray	mask = `noArray()`
	)

§ minMaxLoc() [1/2]

void cv::minMaxLoc	(	InputArray	src,
		CV_OUT double *	minVal,
		CV_OUT double *	maxVal = `0`,
		CV_OUT Point *	minLoc = `0`,
		CV_OUT Point *	maxLoc = `0`,
		InputArray	mask = `noArray()`
	)

finds global minimum and maximum array elements and returns their values and their locations

§ minMaxLoc() [2/2]

void cv::minMaxLoc	(	const SparseMat &	a,
		double *	minVal,
		double *	maxVal,
		int *	minIdx = `0`,
		int *	maxIdx = `0`
	)

finds global minimum and maximum sparse array elements and returns their values and their locations

§ mixChannels() [1/3]

void cv::mixChannels	(	const Mat *	src,
		size_t	nsrcs,
		Mat *	dst,
		size_t	ndsts,
		const int *	fromTo,
		size_t	npairs
	)

copies selected channels from the input arrays to the selected channels of the output arrays

§ mixChannels() [2/3]

void cv::mixChannels	(	const vector< Mat > &	src,
		vector< Mat > &	dst,
		const int *	fromTo,
		size_t	npairs
	)

§ mixChannels() [3/3]

void cv::mixChannels	(	InputArrayOfArrays	src,
		InputArrayOfArrays	dst,
		const vector< int > &	fromTo
	)

§ moments()

Moments cv::moments	(	InputArray	array,
		bool	binaryImage = `false`
	)

computes moments of the rasterized shape or a vector of points

§ morphologyEx()

void cv::morphologyEx	(	InputArray	src,
		OutputArray	dst,
		int	op,
		InputArray	kernel,
		Point	anchor = `Point(-1,-1)`,
		int	iterations = `1`,
		int	borderType = `BORDER_CONSTANT`,
		const Scalar &	borderValue = `morphologyDefaultBorderValue()`
	)

applies an advanced morphological operation to the image

§ moveWindow()

void cv::moveWindow	(	const string &	winname,
		int	x,
		int	y
	)

§ mulSpectrums()

void cv::mulSpectrums	(	InputArray	a,
		InputArray	b,
		OutputArray	c,
		int	flags,
		bool	conjB = `false`
	)

computes element-wise product of the two Fourier spectrums. The second spectrum can optionally be conjugated before the multiplication

§ multiply()

void cv::multiply	(	InputArray	src1,
		InputArray	src2,
		OutputArray	dst,
		double	scale = `1`,
		int	dtype = `-1`
	)

computes element-wise weighted product of the two arrays (dst = scale*src1*src2)

§ mulTransposed()

void cv::mulTransposed	(	InputArray	src,
		OutputArray	dst,
		bool	aTa,
		InputArray	delta = `noArray()`,
		double	scale = `1`,
		int	dtype = `-1`
	)

multiplies matrix by its transposition from the left or from the right

§ namedWindow()

void cv::namedWindow	(	const string &	winname,
		int	flags = `WINDOW_AUTOSIZE`
	)

§ noArray()

OutputArray cv::noArray ( )

§ norm() [1/3]

double cv::norm	(	InputArray	src1,
		int	normType = `NORM_L2`,
		InputArray	mask = `noArray()`
	)

computes norm of the selected array part

§ norm() [2/3]

double cv::norm	(	InputArray	src1,
		InputArray	src2,
		int	normType = `NORM_L2`,
		InputArray	mask = `noArray()`
	)

computes norm of selected part of the difference between two arrays

§ norm() [3/3]

double cv::norm	(	const SparseMat &	src,
		int	normType
	)

computes norm of a sparse matrix

§ normalize() [1/3]

template<typename _Tp , int cn>

Vec<_Tp, cn> cv::normalize ( const Vec< _Tp, cn > & v )

inline

§ normalize() [2/3]

void cv::normalize	(	InputArray	src,
		OutputArray	dst,
		double	alpha = `1`,
		double	beta = `0`,
		int	norm_type = `NORM_L2`,
		int	dtype = `-1`,
		InputArray	mask = `noArray()`
	)

scales and shifts array elements so that either the specified norm (alpha) or the minimum (alpha) and maximum (beta) array values get the specified values

§ normalize() [3/3]

void cv::normalize	(	const SparseMat &	src,
		SparseMat &	dst,
		double	alpha,
		int	normType
	)

scales and shifts array elements so that either the specified norm (alpha) or the minimum (alpha) and maximum (beta) array values get the specified values

§ normHamming() [1/2]

int cv::normHamming	(	const uchar *	a,
		const uchar *	b,
		int	n
	)

§ normHamming() [2/2]

int cv::normHamming	(	const uchar *	a,
		const uchar *	b,
		int	n,
		int	cellSize
	)

§ normL1() [1/2]

template<>

float cv::normL1	(	const float *	a,
		const float *	b,
		int	n
	)

inline

§ normL1() [2/2]

template<>

int cv::normL1	(	const uchar *	a,
		const uchar *	b,
		int	n
	)

inline

§ normL1_() [1/2]

float cv::normL1_	(	const float *	a,
		const float *	b,
		int	n
	)

§ normL1_() [2/2]

int cv::normL1_	(	const uchar *	a,
		const uchar *	b,
		int	n
	)

§ normL2Sqr()

template<>

float cv::normL2Sqr	(	const float *	a,
		const float *	b,
		int	n
	)

inline

§ normL2Sqr_()

float cv::normL2Sqr_	(	const float *	a,
		const float *	b,
		int	n
	)

§ operator!=() [1/4]

MatExpr cv::operator!=	(	const Mat &	a,
		const Mat &	b
	)

§ operator!=() [2/4]

MatExpr cv::operator!=	(	const Mat &	a,
		double	s
	)

§ operator!=() [3/4]

MatExpr cv::operator!=	(	double	s,
		const Mat &	a
	)

§ operator!=() [4/4]

template<typename _Tp >

bool cv::operator!=	(	const SeqIterator< _Tp > &	a,
		const SeqIterator< _Tp > &	b
	)

inline

§ operator&() [1/3]

MatExpr cv::operator &	(	const Mat &	a,
		const Mat &	b
	)

§ operator&() [2/3]

MatExpr cv::operator &	(	const Mat &	a,
		const Scalar &	s
	)

§ operator&() [3/3]

MatExpr cv::operator &	(	const Scalar &	s,
		const Mat &	a
	)

§ operator*() [1/9]

MatExpr cv::operator*	(	const Mat &	a,
		const Mat &	b
	)

§ operator*() [2/9]

MatExpr cv::operator*	(	const Mat &	a,
		double	s
	)

§ operator*() [3/9]

MatExpr cv::operator*	(	double	s,
		const Mat &	a
	)

§ operator*() [4/9]

MatExpr cv::operator*	(	const MatExpr &	e,
		const Mat &	m
	)

§ operator*() [5/9]

MatExpr cv::operator*	(	const Mat &	m,
		const MatExpr &	e
	)

§ operator*() [6/9]

MatExpr cv::operator*	(	const MatExpr &	e,
		double	s
	)

§ operator*() [7/9]

MatExpr cv::operator*	(	double	s,
		const MatExpr &	e
	)

§ operator*() [8/9]

MatExpr cv::operator*	(	const MatExpr &	e1,
		const MatExpr &	e2
	)

§ operator*() [9/9]

template<typename _Tp >

Vec<_Tp, 4> cv::operator*	(	const Vec< _Tp, 4 > &	v1,
		const Vec< _Tp, 4 > &	v2
	)

inline

§ operator*=()

template<typename _Tp >

Vec<_Tp, 4>& cv::operator*=	(	Vec< _Tp, 4 > &	v1,
		const Vec< _Tp, 4 > &	v2
	)

inline

§ operator+() [1/8]

MatExpr cv::operator+	(	const Mat &	a,
		const Mat &	b
	)

§ operator+() [2/8]

MatExpr cv::operator+	(	const Mat &	a,
		const Scalar &	s
	)

§ operator+() [3/8]

MatExpr cv::operator+	(	const Scalar &	s,
		const Mat &	a
	)

§ operator+() [4/8]

MatExpr cv::operator+	(	const MatExpr &	e,
		const Mat &	m
	)

§ operator+() [5/8]

MatExpr cv::operator+	(	const Mat &	m,
		const MatExpr &	e
	)

§ operator+() [6/8]

MatExpr cv::operator+	(	const MatExpr &	e,
		const Scalar &	s
	)

§ operator+() [7/8]

MatExpr cv::operator+	(	const Scalar &	s,
		const MatExpr &	e
	)

§ operator+() [8/8]

MatExpr cv::operator+	(	const MatExpr &	e1,
		const MatExpr &	e2
	)

§ operator-() [1/12]

MatExpr cv::operator-	(	const Mat &	a,
		const Mat &	b
	)

§ operator-() [2/12]

MatExpr cv::operator-	(	const Mat &	a,
		const Scalar &	s
	)

§ operator-() [3/12]

MatExpr cv::operator-	(	const Scalar &	s,
		const Mat &	a
	)

§ operator-() [4/12]

MatExpr cv::operator-	(	const MatExpr &	e,
		const Mat &	m
	)

§ operator-() [5/12]

MatExpr cv::operator-	(	const Mat &	m,
		const MatExpr &	e
	)

§ operator-() [6/12]

MatExpr cv::operator-	(	const MatExpr &	e,
		const Scalar &	s
	)

§ operator-() [7/12]

MatExpr cv::operator-	(	const Scalar &	s,
		const MatExpr &	e
	)

§ operator-() [8/12]

MatExpr cv::operator-	(	const MatExpr &	e1,
		const MatExpr &	e2
	)

§ operator-() [9/12]

MatExpr cv::operator- ( const Mat & m )

§ operator-() [10/12]

MatExpr cv::operator- ( const MatExpr & e )

§ operator-() [11/12]

ptrdiff_t cv::operator-	(	const MatConstIterator &	b,
		const MatConstIterator &	a
	)

§ operator-() [12/12]

template<typename _Tp >

ptrdiff_t cv::operator-	(	const SeqIterator< _Tp > &	a,
		const SeqIterator< _Tp > &	b
	)

inline

§ operator/() [1/8]

MatExpr cv::operator/	(	const Mat &	a,
		const Mat &	b
	)

§ operator/() [2/8]

MatExpr cv::operator/	(	const Mat &	a,
		double	s
	)

§ operator/() [3/8]

MatExpr cv::operator/	(	double	s,
		const Mat &	a
	)

§ operator/() [4/8]

MatExpr cv::operator/	(	const MatExpr &	e,
		const Mat &	m
	)

§ operator/() [5/8]

MatExpr cv::operator/	(	const Mat &	m,
		const MatExpr &	e
	)

§ operator/() [6/8]

MatExpr cv::operator/	(	const MatExpr &	e,
		double	s
	)

§ operator/() [7/8]

MatExpr cv::operator/	(	double	s,
		const MatExpr &	e
	)

§ operator/() [8/8]

MatExpr cv::operator/	(	const MatExpr &	e1,
		const MatExpr &	e2
	)

§ operator<() [1/3]

MatExpr cv::operator<	(	const Mat &	a,
		const Mat &	b
	)

§ operator<() [2/3]

MatExpr cv::operator<	(	const Mat &	a,
		double	s
	)

§ operator<() [3/3]

MatExpr cv::operator<	(	double	s,
		const Mat &	a
	)

§ operator<<() [1/8]

std::ostream& cv::operator<<	(	std::ostream &	out,
		const TickMeter &	tm
	)

§ operator<<() [2/8]

FileStorage& cv::operator<<	(	FileStorage &	fs,
		const string &	str
	)

§ operator<<() [3/8]

template<typename _Tp , int m, int n>

std::ostream& cv::operator<<	(	std::ostream &	out,
		const Matx< _Tp, m, n > &	matx
	)

inline

Writes a Matx to an output stream.

§ operator<<() [4/8]

template<typename _Tp >

std::ostream& cv::operator<<	(	std::ostream &	out,
		const Point_< _Tp > &	p
	)

inline

Writes a point to an output stream in Matlab notation

§ operator<<() [5/8]

template<typename _Tp >

std::ostream& cv::operator<<	(	std::ostream &	out,
		const Point3_< _Tp > &	p
	)

inline

Writes a point to an output stream in Matlab notation

§ operator<<() [6/8]

template<typename _Tp , int n>

std::ostream& cv::operator<<	(	std::ostream &	out,
		const Vec< _Tp, n > &	vec
	)

inline

Writes a Vec to an output stream. Format example : [10, 20, 30]

§ operator<<() [7/8]

template<typename _Tp >

std::ostream& cv::operator<<	(	std::ostream &	out,
		const Size_< _Tp > &	size
	)

inline

Writes a Size_ to an output stream. Format example : [640 x 480]

§ operator<<() [8/8]

template<typename _Tp >

std::ostream& cv::operator<<	(	std::ostream &	out,
		const Rect_< _Tp > &	rect
	)

inline

Writes a Rect_ to an output stream. Format example : [640 x 480 from (10, 20)]

§ operator<=() [1/3]

MatExpr cv::operator<=	(	const Mat &	a,
		const Mat &	b
	)

§ operator<=() [2/3]

MatExpr cv::operator<=	(	const Mat &	a,
		double	s
	)

§ operator<=() [3/3]

MatExpr cv::operator<=	(	double	s,
		const Mat &	a
	)

§ operator==() [1/4]

MatExpr cv::operator==	(	const Mat &	a,
		const Mat &	b
	)

§ operator==() [2/4]

MatExpr cv::operator==	(	const Mat &	a,
		double	s
	)

§ operator==() [3/4]

MatExpr cv::operator==	(	double	s,
		const Mat &	a
	)

§ operator==() [4/4]

template<typename _Tp >

bool cv::operator==	(	const SeqIterator< _Tp > &	a,
		const SeqIterator< _Tp > &	b
	)

inline

§ operator>() [1/3]

MatExpr cv::operator>	(	const Mat &	a,
		const Mat &	b
	)

§ operator>() [2/3]

MatExpr cv::operator>	(	const Mat &	a,
		double	s
	)

§ operator>() [3/3]

MatExpr cv::operator>	(	double	s,
		const Mat &	a
	)

§ operator>=() [1/3]

MatExpr cv::operator>=	(	const Mat &	a,
		const Mat &	b
	)

§ operator>=() [2/3]

MatExpr cv::operator>=	(	const Mat &	a,
		double	s
	)

§ operator>=() [3/3]

MatExpr cv::operator>=	(	double	s,
		const Mat &	a
	)

§ operator^() [1/3]

MatExpr cv::operator^	(	const Mat &	a,
		const Mat &	b
	)

§ operator^() [2/3]

MatExpr cv::operator^	(	const Mat &	a,
		const Scalar &	s
	)

§ operator^() [3/3]

MatExpr cv::operator^	(	const Scalar &	s,
		const Mat &	a
	)

§ operator|() [1/3]

MatExpr cv::operator\|	(	const Mat &	a,
		const Mat &	b
	)

§ operator|() [2/3]

MatExpr cv::operator\|	(	const Mat &	a,
		const Scalar &	s
	)

§ operator|() [3/3]

MatExpr cv::operator\|	(	const Scalar &	s,
		const Mat &	a
	)

§ operator~()

MatExpr cv::operator~ ( const Mat & m )

§ parallel_for_()

void cv::parallel_for_	(	const Range &	range,
		const ParallelLoopBody &	body,
		double	nstripes = `-1.`
	)

§ partition()

template<typename _Tp , class _EqPredicate >

int cv::partition	(	const vector< _Tp > &	_vec,
		vector< int > &	labels,
		_EqPredicate	predicate = `_EqPredicate()`
	)

§ patchNaNs()

void cv::patchNaNs	(	InputOutputArray	a,
		double	val = `0`
	)

converts NaN's to the given number

§ PCABackProject()

void cv::PCABackProject	(	InputArray	data,
		InputArray	mean,
		InputArray	eigenvectors,
		OutputArray	result
	)

§ PCACompute()

void cv::PCACompute	(	InputArray	data,
		CV_OUT InputOutputArray	mean,
		OutputArray	eigenvectors,
		int	maxComponents = `0`
	)

§ PCAComputeVar()

void cv::PCAComputeVar	(	InputArray	data,
		CV_OUT InputOutputArray	mean,
		OutputArray	eigenvectors,
		double	retainedVariance
	)

§ PCAProject()

void cv::PCAProject	(	InputArray	data,
		InputArray	mean,
		InputArray	eigenvectors,
		OutputArray	result
	)

§ perspectiveTransform()

void cv::perspectiveTransform	(	InputArray	src,
		OutputArray	dst,
		InputArray	m
	)

performs perspective transformation of each element of multi-channel input matrix

§ phase()

void cv::phase	(	InputArray	x,
		InputArray	y,
		OutputArray	angle,
		bool	angleInDegrees = `false`
	)

computes angle (angle(i)) of each (x(i), y(i)) vector

§ phaseCorrelate()

Point2d cv::phaseCorrelate	(	InputArray	src1,
		InputArray	src2,
		InputArray	window = `noArray()`
	)

§ phaseCorrelateRes()

Point2d cv::phaseCorrelateRes	(	InputArray	src1,
		InputArray	src2,
		InputArray	window,
		CV_OUT double *	response = `0`
	)

§ pointCloudShow() [1/2]

void cv::pointCloudShow	(	const string &	winname,
		const GlCamera &	camera,
		const GlArrays &	arr
	)

§ pointCloudShow() [2/2]

void cv::pointCloudShow	(	const string &	winname,
		const GlCamera &	camera,
		InputArray	points,
		InputArray	colors = `noArray()`
	)

§ pointPolygonTest()

double cv::pointPolygonTest	(	InputArray	contour,
		Point2f	pt,
		bool	measureDist
	)

checks if the point is inside the contour. Optionally computes the signed distance from the point to the contour boundary

§ polarToCart()

void cv::polarToCart	(	InputArray	magnitude,
		InputArray	angle,
		OutputArray	x,
		OutputArray	y,
		bool	angleInDegrees = `false`
	)

converts polar coordinates to Cartesian

§ polyfit()

void cv::polyfit	(	const Mat &	srcx,
		const Mat &	srcy,
		Mat &	dst,
		int	order
	)

§ polylines() [1/2]

void cv::polylines	(	Mat &	img,
		const Point **	pts,
		const int *	npts,
		int	ncontours,
		bool	isClosed,
		const Scalar &	color,
		int	thickness = `1`,
		int	lineType = `8`,
		int	shift = `0`
	)

draws one or more polygonal curves

§ polylines() [2/2]

void cv::polylines	(	InputOutputArray	img,
		InputArrayOfArrays	pts,
		bool	isClosed,
		const Scalar &	color,
		int	thickness = `1`,
		int	lineType = `8`,
		int	shift = `0`
	)

§ pow()

void cv::pow	(	InputArray	src,
		double	power,
		OutputArray	dst
	)

raises the input matrix elements to the specified power (b = a**power)

§ preCornerDetect()

void cv::preCornerDetect	(	InputArray	src,
		OutputArray	dst,
		int	ksize,
		int	borderType = `BORDER_DEFAULT`
	)

computes another complex cornerness criteria at each pixel

§ process() [1/2]

template<typename T1 , typename T2 , typename Op >

void cv::process	(	const Mat_< T1 > &	m1,
		Mat_< T2 > &	m2,
		Op	op
	)

inline

§ process() [2/2]

template<typename T1 , typename T2 , typename T3 , typename Op >

void cv::process	(	const Mat_< T1 > &	m1,
		const Mat_< T2 > &	m2,
		Mat_< T3 > &	m3,
		Op	op
	)

inline

§ projectPoints()

void cv::projectPoints	(	InputArray	objectPoints,
		InputArray	rvec,
		InputArray	tvec,
		InputArray	cameraMatrix,
		InputArray	distCoeffs,
		OutputArray	imagePoints,
		OutputArray	jacobian = `noArray()`,
		double	aspectRatio = `0`
	)

projects points from the model coordinate space to the image coordinates. Also computes derivatives of the image coordinates w.r.t the intrinsic and extrinsic camera parameters

§ PSNR()

double cv::PSNR	(	InputArray	src1,
		InputArray	src2
	)

computes PSNR image/video quality metric

§ putText()

void cv::putText	(	Mat &	img,
		const string &	text,
		Point	org,
		int	fontFace,
		double	fontScale,
		Scalar	color,
		int	thickness = `1`,
		int	lineType = `8`,
		bool	bottomLeftOrigin = `false`
	)

renders text string in the image

§ pyrDown()

void cv::pyrDown	(	InputArray	src,
		OutputArray	dst,
		const Size &	dstsize = `Size()`,
		int	borderType = `BORDER_DEFAULT`
	)

smooths and downsamples the image

§ pyrMeanShiftFiltering()

void cv::pyrMeanShiftFiltering	(	InputArray	src,
		OutputArray	dst,
		double	sp,
		double	sr,
		int	maxLevel = `1`,
		TermCriteria	termcrit = `TermCriteria(TermCriteria::MAX_ITER+TermCriteria::EPS, 5, 1)`
	)

filters image using meanshift algorithm

§ pyrUp()

void cv::pyrUp	(	InputArray	src,
		OutputArray	dst,
		const Size &	dstsize = `Size()`,
		int	borderType = `BORDER_DEFAULT`
	)

upsamples and smoothes the image

§ randn()

void cv::randn	(	InputOutputArray	dst,
		InputArray	mean,
		InputArray	stddev
	)

fills array with normally-distributed random numbers with the specified mean and the standard deviation

§ randShuffle()

void cv::randShuffle	(	InputOutputArray	dst,
		double	iterFactor = `1.`,
		RNG *	rng = `0`
	)

shuffles the input array elements

§ randu()

void cv::randu	(	InputOutputArray	dst,
		InputArray	low,
		InputArray	high
	)

fills array with uniformly-distributed random numbers from the range [low, high)

§ read() [1/3]

void cv::read	(	const FileNode &	node,
		CV_OUT vector< KeyPoint > &	keypoints
	)

reads vector of keypoints from the specified file storage node

§ read() [2/3]

void cv::read	(	const FileNode &	node,
		Mat &	mat,
		const Mat &	default_mat = `Mat()`
	)

§ read() [3/3]

void cv::read	(	const FileNode &	node,
		SparseMat &	mat,
		const SparseMat &	default_mat = `SparseMat()`
	)

§ rectangle() [1/2]

void cv::rectangle	(	CV_IN_OUT Mat &	img,
		Point	pt1,
		Point	pt2,
		const Scalar &	color,
		int	thickness = `1`,
		int	lineType = `8`,
		int	shift = `0`
	)

draws the rectangle outline or a solid rectangle with the opposite corners pt1 and pt2 in the image

§ rectangle() [2/2]

void cv::rectangle	(	CV_IN_OUT Mat &	img,
		Rect	rec,
		const Scalar &	color,
		int	thickness = `1`,
		int	lineType = `8`,
		int	shift = `0`
	)

draws the rectangle outline or a solid rectangle covering rec in the image

§ rectify3Collinear()

float cv::rectify3Collinear	(	InputArray	cameraMatrix1,
		InputArray	distCoeffs1,
		InputArray	cameraMatrix2,
		InputArray	distCoeffs2,
		InputArray	cameraMatrix3,
		InputArray	distCoeffs3,
		InputArrayOfArrays	imgpt1,
		InputArrayOfArrays	imgpt3,
		Size	imageSize,
		InputArray	R12,
		InputArray	T12,
		InputArray	R13,
		InputArray	T13,
		OutputArray	R1,
		OutputArray	R2,
		OutputArray	R3,
		OutputArray	P1,
		OutputArray	P2,
		OutputArray	P3,
		OutputArray	Q,
		double	alpha,
		Size	newImgSize,
		CV_OUT Rect *	roi1,
		CV_OUT Rect *	roi2,
		int	flags
	)

computes the rectification transformations for 3-head camera, where all the heads are on the same line.

§ redirectError()

ErrorCallback cv::redirectError	(	ErrorCallback	errCallback,
		void *	userdata = `0`,
		void **	prevUserdata = `0`
	)

Sets the new error handler and the optional user data.

The function sets the new error handler, called from cv::error().

Parameters

errCallback	the new error handler. If NULL, the default error handler is used.
userdata	the optional user data pointer, passed to the callback.
prevUserdata	the optional output parameter where the previous user data pointer is stored

Returns: the previous error handler

§ reduce()

void cv::reduce	(	InputArray	src,
		OutputArray	dst,
		int	dim,
		int	rtype,
		int	dtype = `-1`
	)

transforms 2D matrix to 1D row or column vector by taking sum, minimum, maximum or mean value over all the rows

§ remap()

void cv::remap	(	InputArray	src,
		OutputArray	dst,
		InputArray	map1,
		InputArray	map2,
		int	interpolation,
		int	borderMode = `BORDER_CONSTANT`,
		const Scalar &	borderValue = `Scalar()`
	)

warps the image using the precomputed maps. The maps are stored in either floating-point or integer fixed-point format

§ render() [1/3]

void cv::render	(	const GlTexture &	tex,
		Rect_< double >	wndRect = `Rect_< double >(0.0, 0.0, 1.0, 1.0)`,
		Rect_< double >	texRect = `Rect_< double >(0.0, 0.0, 1.0, 1.0)`
	)

render functions

render texture rectangle in window

§ render() [2/3]

void cv::render	(	const GlArrays &	arr,
		int	mode = `RenderMode::POINTS`,
		Scalar	color = `Scalar::all(255)`
	)

render OpenGL arrays

§ render() [3/3]

void cv::render	(	const std::string &	str,
		const Ptr< GlFont > &	font,
		Scalar	color,
		Point2d	pos
	)

§ repeat() [1/2]

void cv::repeat	(	InputArray	src,
		int	ny,
		int	nx,
		OutputArray	dst
	)

replicates the input matrix the specified number of times in the horizontal and/or vertical direction

§ repeat() [2/2]

Mat cv::repeat	(	const Mat &	src,
		int	ny,
		int	nx
	)

§ reprojectImageTo3D()

void cv::reprojectImageTo3D	(	InputArray	disparity,
		OutputArray	_3dImage,
		InputArray	Q,
		bool	handleMissingValues = `false`,
		int	ddepth = `-1`
	)

reprojects disparity image to 3D: (x,y,d)->(X,Y,Z) using the matrix Q returned by cv::stereoRectify

§ resize()

void cv::resize	(	InputArray	src,
		OutputArray	dst,
		Size	dsize,
		double	fx = `0`,
		double	fy = `0`,
		int	interpolation = `INTER_LINEAR`
	)

resizes the image

§ resizeWindow()

void cv::resizeWindow	(	const string &	winname,
		int	width,
		int	height
	)

§ RGBDOdometry()

bool cv::RGBDOdometry	(	Mat &	Rt,
		const Mat &	initRt,
		const Mat &	image0,
		const Mat &	depth0,
		const Mat &	mask0,
		const Mat &	image1,
		const Mat &	depth1,
		const Mat &	mask1,
		const Mat &	cameraMatrix,
		float	minDepth = `0.f`,
		float	maxDepth = `4.f`,
		float	maxDepthDiff = `0.07f`,
		const std::vector< int > &	iterCounts = `std::vector< int >()`,
		const std::vector< float > &	minGradientMagnitudes = `std::vector< float >()`,
		int	transformType = `RIGID_BODY_MOTION`
	)

§ Rodrigues()

void cv::Rodrigues	(	InputArray	src,
		OutputArray	dst,
		OutputArray	jacobian = `noArray()`
	)

converts rotation vector to rotation matrix or vice versa using Rodrigues transformation

§ RQDecomp3x3()

Vec3d cv::RQDecomp3x3	(	InputArray	src,
		OutputArray	mtxR,
		OutputArray	mtxQ,
		OutputArray	Qx = `noArray()`,
		OutputArray	Qy = `noArray()`,
		OutputArray	Qz = `noArray()`
	)

void cv::scalarToRawData	(	const Scalar &	s,
		void *	buf,
		int	type,
		int	unroll_to = `0`
	)

§ scaleAdd()

void cv::scaleAdd	(	InputArray	src1,
		double	alpha,
		InputArray	src2,
		OutputArray	dst
	)

adds scaled array to another one (dst = alpha*src1 + src2)

§ Scharr()

void cv::Scharr	(	InputArray	src,
		OutputArray	dst,
		int	ddepth,
		int	dx,
		int	dy,
		double	scale = `1`,
		double	delta = `0`,
		int	borderType = `BORDER_DEFAULT`
	)

applies the vertical or horizontal Scharr operator to the image

§ segmentMotion()

void cv::segmentMotion	(	InputArray	mhi,
		OutputArray	segmask,
		CV_OUT vector< Rect > &	boundingRects,
		double	timestamp,
		double	segThresh
	)

§ sepFilter2D()

void cv::sepFilter2D	(	InputArray	src,
		OutputArray	dst,
		int	ddepth,
		InputArray	kernelX,
		InputArray	kernelY,
		Point	anchor = `Point(-1,-1)`,
		double	delta = `0`,
		int	borderType = `BORDER_DEFAULT`
	)

applies separable 2D linear filter to the image

§ seqInsertSlice()

void cv::seqInsertSlice	(	CvSeq *	seq,
		int	before_index,
		const CvArr *	from_arr
	)

§ seqPop()

void cv::seqPop	(	CvSeq *	seq,
		void *	element = `0`
	)

§ seqPopFront()

void cv::seqPopFront	(	CvSeq *	seq,
		void *	element = `0`
	)

§ seqPopMulti()

void cv::seqPopMulti	(	CvSeq *	seq,
		void *	elements,
		int	count,
		int	in_front = `0`
	)

§ seqPush()

schar* cv::seqPush	(	CvSeq *	seq,
		const void *	element = `0`
	)

§ seqPushFront()

schar* cv::seqPushFront	(	CvSeq *	seq,
		const void *	element = `0`
	)

§ seqRemove()

void cv::seqRemove	(	CvSeq *	seq,
		int	index
	)

§ seqRemoveSlice()

void cv::seqRemoveSlice	(	CvSeq *	seq,
		CvSlice	slice
	)

§ setBreakOnError()

bool cv::setBreakOnError ( bool flag )

Sets/resets the break-on-error mode.

When the break-on-error mode is set, the default error handler issues a hardware exception, which can make debugging more convenient.

Returns: the previous state

§ setIdentity()

void cv::setIdentity	(	InputOutputArray	mtx,
		const Scalar &	s = `Scalar(1)`
	)

initializes scaled identity matrix

§ setMouseCallback()

void cv::setMouseCallback	(	const string &	winname,
		MouseCallback	onMouse,
		void *	userdata = `0`
	)

assigns callback for mouse events

§ setNumThreads()

void cv::setNumThreads ( int nthreads )

§ setOpenGlContext()

void cv::setOpenGlContext ( const string & winname )

§ setOpenGlDrawCallback()

void cv::setOpenGlDrawCallback	(	const string &	winname,
		OpenGlDrawCallback	onOpenGlDraw,
		void *	userdata = `0`
	)

§ setRNGSeed()

void cv::setRNGSeed ( int seed )

sets state of the thread-local Random number generator

§ setTrackbarPos()

void cv::setTrackbarPos	(	const string &	trackbarname,
		const string &	winname,
		int	pos
	)

§ setUseOptimized()

void cv::setUseOptimized ( bool onoff )

Turns on/off available optimization

The function turns on or off the optimized code in OpenCV. Some optimization can not be enabled or disabled, but, for example, most of SSE code in OpenCV can be temporarily turned on or off this way.

Note: {Since optimization may imply using special data structures, it may be unsafe to call this function anywhere in the code. Instead, call it somewhere at the top level.}

§ setWindowProperty()

void cv::setWindowProperty	(	const string &	winname,
		int	prop_id,
		double	prop_value
	)

§ Sobel()

void cv::Sobel	(	InputArray	src,
		OutputArray	dst,
		int	ddepth,
		int	dx,
		int	dy,
		int	ksize = `3`,
		double	scale = `1`,
		double	delta = `0`,
		int	borderType = `BORDER_DEFAULT`
	)

applies generalized Sobel operator to the image

§ solve()

bool cv::solve	(	InputArray	src1,
		InputArray	src2,
		OutputArray	dst,
		int	flags = `DECOMP_LU`
	)

solves linear system or a least-square problem

§ solveCubic()

int cv::solveCubic	(	InputArray	coeffs,
		OutputArray	roots
	)

finds real roots of a cubic polynomial

§ solvePnP()

bool cv::solvePnP	(	InputArray	objectPoints,
		InputArray	imagePoints,
		InputArray	cameraMatrix,
		InputArray	distCoeffs,
		OutputArray	rvec,
		OutputArray	tvec,
		bool	useExtrinsicGuess = `false`,
		int	flags = `ITERATIVE`
	)

§ solvePnPRansac()

void cv::solvePnPRansac	(	InputArray	objectPoints,
		InputArray	imagePoints,
		InputArray	cameraMatrix,
		InputArray	distCoeffs,
		OutputArray	rvec,
		OutputArray	tvec,
		bool	useExtrinsicGuess = `false`,
		int	iterationsCount = `100`,
		float	reprojectionError = `8.0`,
		int	minInliersCount = `100`,
		OutputArray	inliers = `noArray()`,
		int	flags = `ITERATIVE`
	)

computes the camera pose from a few 3D points and the corresponding projections. The outliers are possible.

§ solvePoly()

double cv::solvePoly	(	InputArray	coeffs,
		OutputArray	roots,
		int	maxIters = `300`
	)

finds real and complex roots of a polynomial

§ sort() [1/2]

void cv::sort	(	InputArray	src,
		OutputArray	dst,
		int	flags
	)

sorts independently each matrix row or each matrix column

§ sort() [2/2]

template<typename _Tp , class _LT >

void cv::sort	(	vector< _Tp > &	vec,
		_LT	LT = `_LT()`
	)

§ sortIdx()

void cv::sortIdx	(	InputArray	src,
		OutputArray	dst,
		int	flags
	)

sorts independently each matrix row or each matrix column

§ split() [1/4]

template<typename _Tp >

void cv::split	(	const Mat &	src,
		vector< Mat_< _Tp > > &	mv
	)

§ split() [2/4]

void cv::split	(	const Mat &	src,
		Mat *	mvbegin
	)

copies each plane of a multi-channel array to a dedicated array

§ split() [3/4]

void cv::split	(	const Mat &	m,
		vector< Mat > &	mv
	)

§ split() [4/4]

void cv::split	(	InputArray	m,
		OutputArrayOfArrays	mv
	)

copies each plane of a multi-channel array to a dedicated array

§ sqrt()

void cv::sqrt	(	InputArray	src,
		OutputArray	dst
	)

computes square root of each matrix element (dst = src**0.5)

§ startLoop()

int cv::startLoop	(	int()(int argc, char argv[])	pt2Func,
		int	argc,
		char *	argv[]
	)

§ startWindowThread()

int cv::startWindowThread ( )

§ stereoCalibrate()

double cv::stereoCalibrate	(	InputArrayOfArrays	objectPoints,
		InputArrayOfArrays	imagePoints1,
		InputArrayOfArrays	imagePoints2,
		CV_OUT InputOutputArray	cameraMatrix1,
		CV_OUT InputOutputArray	distCoeffs1,
		CV_OUT InputOutputArray	cameraMatrix2,
		CV_OUT InputOutputArray	distCoeffs2,
		Size	imageSize,
		OutputArray	R,
		OutputArray	T,
		OutputArray	E,
		OutputArray	F,
		TermCriteria	criteria = `TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, 30, 1e-6)`,
		int	flags = `CALIB_FIX_INTRINSIC`
	)

finds intrinsic and extrinsic parameters of a stereo camera

§ stereoRectify()

void cv::stereoRectify	(	InputArray	cameraMatrix1,
		InputArray	distCoeffs1,
		InputArray	cameraMatrix2,
		InputArray	distCoeffs2,
		Size	imageSize,
		InputArray	R,
		InputArray	T,
		OutputArray	R1,
		OutputArray	R2,
		OutputArray	P1,
		OutputArray	P2,
		OutputArray	Q,
		int	flags = `CALIB_ZERO_DISPARITY`,
		double	alpha = `-1`,
		Size	newImageSize = `Size()`,
		CV_OUT Rect *	validPixROI1 = `0`,
		CV_OUT Rect *	validPixROI2 = `0`
	)

computes the rectification transformation for a stereo camera from its intrinsic and extrinsic parameters

§ stereoRectifyUncalibrated()

bool cv::stereoRectifyUncalibrated	(	InputArray	points1,
		InputArray	points2,
		InputArray	F,
		Size	imgSize,
		OutputArray	H1,
		OutputArray	H2,
		double	threshold = `5`
	)

computes the rectification transformation for an uncalibrated stereo camera (zero distortion is assumed)

§ stopLoop()

void cv::stopLoop ( )

§ subspaceProject()

Mat cv::subspaceProject	(	InputArray	W,
		InputArray	mean,
		InputArray	src
	)

§ subspaceReconstruct()

Mat cv::subspaceReconstruct	(	InputArray	W,
		InputArray	mean,
		InputArray	src
	)

§ subtract()

void cv::subtract	(	InputArray	src1,
		InputArray	src2,
		OutputArray	dst,
		InputArray	mask = `noArray()`,
		int	dtype = `-1`
	)

subtracts one matrix from another (dst = src1 - src2)

§ SVBackSubst()

void cv::SVBackSubst	(	InputArray	w,
		InputArray	u,
		InputArray	vt,
		InputArray	rhs,
		CV_OUT OutputArray	dst
	)

performs back substitution for the previously computed SVD

§ SVDecomp()

void cv::SVDecomp	(	InputArray	src,
		CV_OUT OutputArray	w,
		CV_OUT OutputArray	u,
		CV_OUT OutputArray	vt,
		int	flags = `0`
	)

computes SVD of src

§ swap()

void cv::swap	(	Mat &	a,
		Mat &	b
	)

swaps two matrices

§ tempfile()

string cv::tempfile ( const char *suffix CV_DEFAULT0 )

§ theRNG()

RNG& cv::theRNG ( )

returns the thread-local Random number generator

§ threshold()

double cv::threshold	(	InputArray	src,
		OutputArray	dst,
		double	thresh,
		double	maxval,
		int	type
	)

applies fixed threshold to the image

§ toUtf16()

WString cv::toUtf16 ( const string & str )

§ trace()

Scalar cv::trace ( InputArray mtx )

computes trace of a matrix

§ transform()

void cv::transform	(	InputArray	src,
		OutputArray	dst,
		InputArray	m
	)

performs affine transformation of each element of multi-channel input matrix

§ transpose()

void cv::transpose	(	InputArray	src,
		OutputArray	dst
	)

transposes the matrix

§ triangulatePoints()

void cv::triangulatePoints	(	InputArray	projMatr1,
		InputArray	projMatr2,
		InputArray	projPoints1,
		InputArray	projPoints2,
		OutputArray	points4D
	)

§ undistort()

void cv::undistort	(	InputArray	src,
		OutputArray	dst,
		InputArray	cameraMatrix,
		InputArray	distCoeffs,
		InputArray	newCameraMatrix = `noArray()`
	)

corrects lens distortion for the given camera matrix and distortion coefficients

§ undistortPoints()

void cv::undistortPoints	(	InputArray	src,
		OutputArray	dst,
		InputArray	cameraMatrix,
		InputArray	distCoeffs,
		InputArray	R = `noArray()`,
		InputArray	P = `noArray()`
	)

returns points' coordinates after lens distortion correction

§ updateMotionHistory()

void cv::updateMotionHistory	(	InputArray	silhouette,
		InputOutputArray	mhi,
		double	timestamp,
		double	duration
	)

updates motion history image using the current silhouette

§ updateWindow()

void cv::updateWindow ( const string & winname )

§ useOptimized()

bool cv::useOptimized ( )

Returns the current optimization status

The function returns the current optimization status, which is controlled by cv::setUseOptimized().

§ validateDisparity()

void cv::validateDisparity	(	InputOutputArray	disparity,
		InputArray	cost,
		int	minDisparity,
		int	numberOfDisparities,
		int	disp12MaxDisp = `1`
	)

validates disparity using the left-right check. The matrix "cost" should be computed by the stereo correspondence algorithm

§ vconcat() [1/3]

void cv::vconcat	(	const Mat *	src,
		size_t	nsrc,
		OutputArray	dst
	)

§ vconcat() [2/3]

void cv::vconcat	(	InputArray	src1,
		InputArray	src2,
		OutputArray	dst
	)

§ vconcat() [3/3]

void cv::vconcat	(	InputArrayOfArrays	src,
		OutputArray	dst
	)

§ waitKey()

int cv::waitKey ( int delay = 0 )

§ warpAffine()

void cv::warpAffine	(	InputArray	src,
		OutputArray	dst,
		InputArray	M,
		Size	dsize,
		int	flags = `INTER_LINEAR`,
		int	borderMode = `BORDER_CONSTANT`,
		const Scalar &	borderValue = `Scalar()`
	)

warps the image using affine transformation

§ warpPerspective()

void cv::warpPerspective	(	InputArray	src,
		OutputArray	dst,
		InputArray	M,
		Size	dsize,
		int	flags = `INTER_LINEAR`,
		int	borderMode = `BORDER_CONSTANT`,
		const Scalar &	borderValue = `Scalar()`
	)

warps the image using perspective transformation

§ watershed()

void cv::watershed	(	InputArray	image,
		InputOutputArray	markers
	)

segments the image using watershed algorithm

§ windowedMatchingMask()

Mat cv::windowedMatchingMask	(	const vector< KeyPoint > &	keypoints1,
		const vector< KeyPoint > &	keypoints2,
		float	maxDeltaX,
		float	maxDeltaY
	)

§ write() [1/28]

void cv::write	(	FileStorage &	fs,
		const string &	name,
		const vector< KeyPoint > &	keypoints
	)

writes vector of keypoints to the file storage

§ write() [2/28]

void cv::write	(	FileStorage &	fs,
		const string &	name,
		int	value
	)

§ write() [3/28]

void cv::write	(	FileStorage &	fs,
		const string &	name,
		float	value
	)

§ write() [4/28]

void cv::write	(	FileStorage &	fs,
		const string &	name,
		double	value
	)

§ write() [5/28]

void cv::write	(	FileStorage &	fs,
		const string &	name,
		const string &	value
	)

§ write() [6/28]

template<typename _Tp >

void cv::write	(	FileStorage &	fs,
		const _Tp &	value
	)

inline

§ write() [7/28]

template<>

void cv::write	(	FileStorage &	fs,
		const int &	value
	)

inline

§ write() [8/28]

template<>

void cv::write	(	FileStorage &	fs,
		const float &	value
	)

inline

§ write() [9/28]

template<>

void cv::write	(	FileStorage &	fs,
		const double &	value
	)

inline

§ write() [10/28]

template<>

void cv::write	(	FileStorage &	fs,
		const string &	value
	)

inline

§ write() [11/28]

template<typename _Tp >

void cv::write	(	FileStorage &	fs,
		const Point_< _Tp > &	pt
	)

inline

§ write() [12/28]

template<typename _Tp >

void cv::write	(	FileStorage &	fs,
		const Point3_< _Tp > &	pt
	)

inline

§ write() [13/28]

template<typename _Tp >

void cv::write	(	FileStorage &	fs,
		const Size_< _Tp > &	sz
	)

inline

§ write() [14/28]

template<typename _Tp >

void cv::write	(	FileStorage &	fs,
		const Complex< _Tp > &	c
	)

inline

§ write() [15/28]

template<typename _Tp >

void cv::write	(	FileStorage &	fs,
		const Rect_< _Tp > &	r
	)

inline

§ write() [16/28]

template<typename _Tp , int cn>

void cv::write	(	FileStorage &	fs,
		const Vec< _Tp, cn > &	v
	)

inline

§ write() [17/28]

template<typename _Tp >

void cv::write	(	FileStorage &	fs,
		const Scalar_< _Tp > &	s
	)

inline

§ write() [18/28]

void cv::write	(	FileStorage &	fs,
		const Range &	r
	)

inline

§ write() [19/28]

template<typename _Tp >

void cv::write	(	FileStorage &	fs,
		const string &	name,
		const Point_< _Tp > &	pt
	)

inline

§ write() [20/28]

template<typename _Tp >

void cv::write	(	FileStorage &	fs,
		const string &	name,
		const Point3_< _Tp > &	pt
	)

inline

§ write() [21/28]

template<typename _Tp >

void cv::write	(	FileStorage &	fs,
		const string &	name,
		const Size_< _Tp > &	sz
	)

inline

§ write() [22/28]

template<typename _Tp >

void cv::write	(	FileStorage &	fs,
		const string &	name,
		const Complex< _Tp > &	c
	)

inline

§ write() [23/28]

template<typename _Tp >

void cv::write	(	FileStorage &	fs,
		const string &	name,
		const Rect_< _Tp > &	r
	)

inline

§ write() [24/28]

template<typename _Tp , int cn>

void cv::write	(	FileStorage &	fs,
		const string &	name,
		const Vec< _Tp, cn > &	v
	)

inline

§ write() [25/28]

template<typename _Tp >

void cv::write	(	FileStorage &	fs,
		const string &	name,
		const Scalar_< _Tp > &	s
	)

inline

§ write() [26/28]

void cv::write	(	FileStorage &	fs,
		const string &	name,
		const Range &	r
	)

inline

§ write() [27/28]

void cv::write	(	FileStorage &	fs,
		const string &	name,
		const Mat &	value
	)

§ write() [28/28]

void cv::write	(	FileStorage &	fs,
		const string &	name,
		const SparseMat &	value
	)

§ writeScalar() [1/4]

void cv::writeScalar	(	FileStorage &	fs,
		int	value
	)

§ writeScalar() [2/4]

void cv::writeScalar	(	FileStorage &	fs,
		float	value
	)

§ writeScalar() [3/4]

void cv::writeScalar	(	FileStorage &	fs,
		double	value
	)

§ writeScalar() [4/4]

void cv::writeScalar	(	FileStorage &	fs,
		const string &	value
	)

Variable Documentation

§ distanceType

OutputArray OutputArray int cv::distanceType

§ dst

OutputArray cv::dst

§ iterFactor

double cv::iterFactor =1.)

§ labels

OutputArray OutputArray cv::labels

§ labelType

OutputArray OutputArray int int int cv::labelType =DIST_LABEL_CCOMP )

§ maskSize

OutputArray OutputArray int int cv::maskSize

§ sdepth

OutputArray OutputArray OutputArray int cv::sdepth =-1 )

§ sqsum

OutputArray OutputArray cv::sqsum

§ sum

OutputArray cv::sum

§ tilted

OutputArray OutputArray OutputArray cv::tilted

Namespaces

Classes

Typedefs

Enumerations

Functions

Variables

Detailed Description

Typedef Documentation

§ Affine3d

§ Affine3f

§ ANN_MLP_TrainParams

§ BinaryFunc

§ Boost

§ BoostParams

§ BoostTree

§ BundleAdjustCallback

§ ButtonCallback

§ Complexd

§ Complexf

§ ConcurrentDoubleVector

§ ConcurrentRectVector

§ ConvertData

§ ConvertScaleData

§ DecisionTree

§ DTreeParams

§ EMParams

§ ErrorCallback

§ ERTree

§ ERTrees

§ ERTreeTRainData

§ ExpectationMaximization

§ FeatureTracker

§ FeatureTrackerParams

§ FernDescriptorMatch

§ ForestTree

§ GenericDescriptorMatch

§ GoodFeaturesToTrackDetector

§ GradientBoostingTreeParams

§ GradientBoostingTrees

§ HammingLUT

§ HybridTracker

§ HybridTrackerParams

§ InputArray

§ InputArrayOfArrays

§ InputOutputArray

§ InputOutputArrayOfArrays

§ KNearest

§ Mat1b

§ Mat1d

§ Mat1f

§ Mat1i

§ Mat1s

§ Mat1w

§ Mat2b

§ Mat2d

§ Mat2f

§ Mat2i

§ Mat2s

§ Mat2w

§ Mat3b

§ Mat3d

§ Mat3f

§ Mat3i

§ Mat3s

§ Mat3w

§ Mat4b

§ Mat4d

§ Mat4f

§ Mat4i

§ Mat4s

§ Mat4w

§ MatND

§ Matx12d

§ Matx12f

§ Matx13d

§ Matx13f

§ Matx14d

§ Matx14f

§ Matx16d

§ Matx16f