cv::xfeatures2d::SURF Class Reference

Class for extracting Speeded Up Robust Features from an image [20] . More...

#include <opencv2/xfeatures2d/nonfree.hpp>

Collaboration diagram for cv::xfeatures2d::SURF:

Public Member Functions
String	getDefaultName () const CV_OVERRIDE
virtual bool	getExtended () const =0
virtual double	getHessianThreshold () const =0
virtual int	getNOctaveLayers () const =0
virtual int	getNOctaves () const =0
virtual bool	getUpright () const =0
virtual void	setExtended (bool extended)=0
virtual void	setHessianThreshold (double hessianThreshold)=0
virtual void	setNOctaveLayers (int nOctaveLayers)=0
virtual void	setNOctaves (int nOctaves)=0
virtual void	setUpright (bool upright)=0
Public Member Functions inherited from cv::Feature2D
virtual	~Feature2D ()
virtual void	compute (InputArray image, std::vector< KeyPoint > &keypoints, OutputArray descriptors)
	Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).
virtual void	compute (InputArrayOfArrays images, std::vector< std::vector< KeyPoint > > &keypoints, OutputArrayOfArrays descriptors)
virtual int	defaultNorm () const
virtual int	descriptorSize () const
virtual int	descriptorType () const
virtual void	detect (InputArray image, std::vector< KeyPoint > &keypoints, InputArray mask=noArray())
	Detects keypoints in an image (first variant) or image set (second variant).
virtual void	detect (InputArrayOfArrays images, std::vector< std::vector< KeyPoint > > &keypoints, InputArrayOfArrays masks=noArray())
virtual void	detectAndCompute (InputArray image, InputArray mask, std::vector< KeyPoint > &keypoints, OutputArray descriptors, bool useProvidedKeypoints=false)
virtual bool	empty () const CV_OVERRIDE
	Return true if detector object is empty.
virtual void	read (const FileNode &) CV_OVERRIDE
	Reads algorithm parameters from a file storage.
void	read (const String &fileName)
void	write (const Ptr< FileStorage > &fs, const String &name) const
void	write (const String &fileName) const
virtual void	write (FileStorage &) const CV_OVERRIDE
	Stores algorithm parameters in a file storage.
void	write (FileStorage &fs, const String &name) const
Public Member Functions inherited from cv::Algorithm
	Algorithm ()
virtual	~Algorithm ()
virtual void	clear ()
	Clears the algorithm state.
virtual void	save (const String &filename) const
void	write (const Ptr< FileStorage > &fs, const String &name=String()) const
void	write (FileStorage &fs, const String &name) const

Static Public Member Functions
static Ptr< SURF >	create (double hessianThreshold=100, int nOctaves=4, int nOctaveLayers=3, bool extended=false, bool upright=false)
Static Public Member Functions inherited from cv::Algorithm
template<typename _Tp >
static Ptr< _Tp >	load (const String &filename, const String &objname=String())
	Loads algorithm from the file.
template<typename _Tp >
static Ptr< _Tp >	loadFromString (const String &strModel, const String &objname=String())
	Loads algorithm from a String.
template<typename _Tp >
static Ptr< _Tp >	read (const FileNode &fn)
	Reads algorithm from the file node.

Additional Inherited Members
Protected Member Functions inherited from cv::Algorithm
void	writeFormat (FileStorage &fs) const

Detailed Description

Class for extracting Speeded Up Robust Features from an image [20] .

The algorithm parameters:

• member int extended
  • 0 means that the basic descriptors (64 elements each) shall be computed
  • 1 means that the extended descriptors (128 elements each) shall be computed
• member int upright
  • 0 means that detector computes orientation of each feature.
  • 1 means that the orientation is not computed (which is much, much faster). For example, if you match images from a stereo pair, or do image stitching, the matched features likely have very similar angles, and you can speed up feature extraction by setting upright=1.
• member double hessianThreshold Threshold for the keypoint detector. Only features, whose hessian is larger than hessianThreshold are retained by the detector. Therefore, the larger the value, the less keypoints you will get. A good default value could be from 300 to 500, depending from the image contrast.
• member int nOctaves The number of a gaussian pyramid octaves that the detector uses. It is set to 4 by default. If you want to get very large features, use the larger value. If you want just small features, decrease it.
• member int nOctaveLayers The number of images within each octave of a gaussian pyramid. It is set to 2 by default.

  Note

  • An example using the SURF feature detector can be found at opencv_source_code/samples/cpp/generic_descriptor_match.cpp
    • Another example using the SURF feature detector, extractor and matcher can be found at opencv_source_code/samples/cpp/matcher_simple.cpp

Member Function Documentation

create()

static Ptr< SURF > cv::xfeatures2d::SURF::create ( double hessianThreshold = 100, int nOctaves = 4, int nOctaveLayers = 3, bool extended = false, bool upright = false )

static

Python:
	cv.xfeatures2d.SURF.create(	[, hessianThreshold[, nOctaves[, nOctaveLayers[, extended[, upright]]]]]	) ->	retval
	cv.xfeatures2d.SURF_create(	[, hessianThreshold[, nOctaves[, nOctaveLayers[, extended[, upright]]]]]	) ->	retval

Parameters

hessianThreshold	Threshold for hessian keypoint detector used in SURF.
nOctaves	Number of pyramid octaves the keypoint detector will use.
nOctaveLayers	Number of octave layers within each octave.
extended	Extended descriptor flag (true - use extended 128-element descriptors; false - use 64-element descriptors).
upright	Up-right or rotated features flag (true - do not compute orientation of features; false - compute orientation).

getDefaultName()

String cv::xfeatures2d::SURF::getDefaultName ( ) const

virtual

Python:
	cv.xfeatures2d.SURF.getDefaultName(		) ->	retval

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

Reimplemented from cv::Feature2D.

getExtended()

virtual bool cv::xfeatures2d::SURF::getExtended ( ) const

pure virtual

Python:
	cv.xfeatures2d.SURF.getExtended(		) ->	retval

getHessianThreshold()

virtual double cv::xfeatures2d::SURF::getHessianThreshold ( ) const

pure virtual

Python:
	cv.xfeatures2d.SURF.getHessianThreshold(		) ->	retval

getNOctaveLayers()

virtual int cv::xfeatures2d::SURF::getNOctaveLayers ( ) const

pure virtual

Python:
	cv.xfeatures2d.SURF.getNOctaveLayers(		) ->	retval

getNOctaves()

virtual int cv::xfeatures2d::SURF::getNOctaves ( ) const

pure virtual

Python:
	cv.xfeatures2d.SURF.getNOctaves(		) ->	retval

getUpright()

virtual bool cv::xfeatures2d::SURF::getUpright ( ) const

pure virtual

Python:
	cv.xfeatures2d.SURF.getUpright(		) ->	retval

setExtended()

virtual void cv::xfeatures2d::SURF::setExtended ( bool extended )

pure virtual

Python:
	cv.xfeatures2d.SURF.setExtended(	extended	) ->	None

setHessianThreshold()

virtual void cv::xfeatures2d::SURF::setHessianThreshold ( double hessianThreshold )

pure virtual

Python:
	cv.xfeatures2d.SURF.setHessianThreshold(	hessianThreshold	) ->	None

setNOctaveLayers()

virtual void cv::xfeatures2d::SURF::setNOctaveLayers ( int nOctaveLayers )

pure virtual

Python:
	cv.xfeatures2d.SURF.setNOctaveLayers(	nOctaveLayers	) ->	None

setNOctaves()

virtual void cv::xfeatures2d::SURF::setNOctaves ( int nOctaves )

pure virtual

Python:
	cv.xfeatures2d.SURF.setNOctaves(	nOctaves	) ->	None

setUpright()

virtual void cv::xfeatures2d::SURF::setUpright ( bool upright )

pure virtual

Python:
	cv.xfeatures2d.SURF.setUpright(	upright	) ->	None

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The documentation for this class was generated from the following file:

• opencv2/xfeatures2d/nonfree.hpp