OpenCV  4.1.2-dev
Open Source Computer Vision
Classes | Functions
Experimental 2D Features Algorithms

Classes

class  cv::xfeatures2d::AffineFeature2D
 Class implementing affine adaptation for key points. More...
 
class  cv::xfeatures2d::BoostDesc
 Class implementing BoostDesc (Learning Image Descriptors with Boosting), described in [207] and [208]. More...
 
class  cv::xfeatures2d::BriefDescriptorExtractor
 Class for computing BRIEF descriptors described in [33] . More...
 
class  cv::xfeatures2d::DAISY
 Class implementing DAISY descriptor, described in [214]. More...
 
class  cv::xfeatures2d::Elliptic_KeyPoint
 Elliptic region around an interest point. More...
 
class  cv::xfeatures2d::FREAK
 Class implementing the FREAK (Fast Retina Keypoint) keypoint descriptor, described in [4] . More...
 
class  cv::xfeatures2d::HarrisLaplaceFeatureDetector
 Class implementing the Harris-Laplace feature detector as described in [152]. More...
 
class  cv::xfeatures2d::LATCH
 
class  cv::xfeatures2d::LUCID
 Class implementing the locally uniform comparison image descriptor, described in [256]. More...
 
class  cv::xfeatures2d::MSDDetector
 Class implementing the MSD (Maximal Self-Dissimilarity) keypoint detector, described in [215]. More...
 
class  cv::xfeatures2d::PCTSignatures
 Class implementing PCT (position-color-texture) signature extraction as described in [116]. The algorithm is divided to a feature sampler and a clusterizer. Feature sampler produces samples at given set of coordinates. Clusterizer then produces clusters of these samples using k-means algorithm. Resulting set of clusters is the signature of the input image. More...
 
class  cv::xfeatures2d::PCTSignaturesSQFD
 Class implementing Signature Quadratic Form Distance (SQFD). More...
 
class  cv::xfeatures2d::StarDetector
 The class implements the keypoint detector introduced by [2], synonym of StarDetector. : More...
 
class  cv::xfeatures2d::VGG
 Class implementing VGG (Oxford Visual Geometry Group) descriptor trained end to end using "Descriptor Learning Using Convex Optimisation" (DLCO) aparatus described in [197]. More...
 

Functions

void cv::xfeatures2d::FASTForPointSet (InputArray image, std::vector< KeyPoint > &keypoints, int threshold, bool nonmaxSuppression=true, cv::FastFeatureDetector::DetectorType type=FastFeatureDetector::TYPE_9_16)
 Estimates cornerness for prespecified KeyPoints using the FAST algorithm. More...
 

Detailed Description

This section describes experimental algorithms for 2d feature detection.

Function Documentation

§ FASTForPointSet()

void cv::xfeatures2d::FASTForPointSet ( InputArray  image,
std::vector< KeyPoint > &  keypoints,
int  threshold,
bool  nonmaxSuppression = true,
cv::FastFeatureDetector::DetectorType  type = FastFeatureDetector::TYPE_9_16 
)

#include <opencv2/xfeatures2d.hpp>

Estimates cornerness for prespecified KeyPoints using the FAST algorithm.

Parameters
imagegrayscale image where keypoints (corners) are detected.
keypointskeypoints which should be tested to fit the FAST criteria. Keypoints not beeing detected as corners are removed.
thresholdthreshold on difference between intensity of the central pixel and pixels of a circle around this pixel.
nonmaxSuppressionif true, non-maximum suppression is applied to detected corners (keypoints).
typeone of the three neighborhoods as defined in the paper: FastFeatureDetector::TYPE_9_16, FastFeatureDetector::TYPE_7_12, FastFeatureDetector::TYPE_5_8

Detects corners using the FAST algorithm by [183] .