Uses of Class
org.opencv.features2d.Feature2D

Packages that use Feature2D

Package	Description
org.opencv.features2d
org.opencv.xfeatures2d

Uses of Feature2D in org.opencv.features2d

Subclasses of Feature2D in org.opencv.features2d

Modifier and Type	Class	Description
class	AffineFeature	Class for implementing the wrapper which makes detectors and extractors to be affine invariant, described as ASIFT in CITE: YM11 .
class	AgastFeatureDetector	Wrapping class for feature detection using the AGAST method.
class	AKAZE	Class implementing the AKAZE keypoint detector and descriptor extractor, described in CITE: ANB13.
class	BRISK	Class implementing the BRISK keypoint detector and descriptor extractor, described in CITE: LCS11 .
class	FastFeatureDetector	Wrapping class for feature detection using the FAST method.
class	GFTTDetector	Wrapping class for feature detection using the goodFeaturesToTrack function.
class	KAZE	Class implementing the KAZE keypoint detector and descriptor extractor, described in CITE: ABD12 .
class	MSER	Maximally stable extremal region extractor The class encapsulates all the parameters of the %MSER extraction algorithm (see [wiki article](http://en.wikipedia.org/wiki/Maximally_stable_extremal_regions)).
class	ORB	Class implementing the ORB (*oriented BRIEF*) keypoint detector and descriptor extractor described in CITE: RRKB11 .
class	SIFT	Class for extracting keypoints and computing descriptors using the Scale Invariant Feature Transform (SIFT) algorithm by D.
class	SimpleBlobDetector	Class for extracting blobs from an image.

Methods in org.opencv.features2d that return Feature2D

Modifier and Type	Method	Description
static Feature2D	Feature2D.__fromPtr__(long addr)

Methods in org.opencv.features2d with parameters of type Feature2D

Modifier and Type	Method	Description
static AffineFeature	AffineFeature.create(Feature2D backend)
static AffineFeature	AffineFeature.create(Feature2D backend, int maxTilt)
static AffineFeature	AffineFeature.create(Feature2D backend, int maxTilt, int minTilt)
static AffineFeature	AffineFeature.create(Feature2D backend, int maxTilt, int minTilt, float tiltStep)
static AffineFeature	AffineFeature.create(Feature2D backend, int maxTilt, int minTilt, float tiltStep, float rotateStepBase)

Uses of Feature2D in org.opencv.xfeatures2d

Subclasses of Feature2D in org.opencv.xfeatures2d

Modifier and Type	Class	Description
class	AffineFeature2D	Class implementing affine adaptation for key points.
class	BEBLID	Class implementing BEBLID (Boosted Efficient Binary Local Image Descriptor), described in CITE: Suarez2020BEBLID .
class	BoostDesc	Class implementing BoostDesc (Learning Image Descriptors with Boosting), described in CITE: Trzcinski13a and CITE: Trzcinski13b.
class	BriefDescriptorExtractor	Class for computing BRIEF descriptors described in CITE: calon2010 .
class	DAISY	Class implementing DAISY descriptor, described in CITE: Tola10 radius radius of the descriptor at the initial scale q_radius amount of radial range division quantity q_theta amount of angular range division quantity q_hist amount of gradient orientations range division quantity norm choose descriptors normalization type, where DAISY::NRM_NONE will not do any normalization (default), DAISY::NRM_PARTIAL mean that histograms are normalized independently for L2 norm equal to 1.0, DAISY::NRM_FULL mean that descriptors are normalized for L2 norm equal to 1.0, DAISY::NRM_SIFT mean that descriptors are normalized for L2 norm equal to 1.0 but no individual one is bigger than 0.154 as in SIFT H optional 3x3 homography matrix used to warp the grid of daisy but sampling keypoints remains unwarped on image interpolation switch to disable interpolation for speed improvement at minor quality loss use_orientation sample patterns using keypoints orientation, disabled by default.
class	FREAK	Class implementing the FREAK (*Fast Retina Keypoint*) keypoint descriptor, described in CITE: AOV12 .
class	HarrisLaplaceFeatureDetector	Class implementing the Harris-Laplace feature detector as described in CITE: Mikolajczyk2004.
class	LATCH	latch Class for computing the LATCH descriptor.
class	LUCID	Class implementing the locally uniform comparison image descriptor, described in CITE: LUCID An image descriptor that can be computed very fast, while being about as robust as, for example, SURF or BRIEF.
class	MSDDetector	Class implementing the MSD (*Maximal Self-Dissimilarity*) keypoint detector, described in CITE: Tombari14.
class	StarDetector	The class implements the keypoint detector introduced by CITE: Agrawal08, synonym of StarDetector.
class	SURF	Class for extracting Speeded Up Robust Features from an image CITE: Bay06 .
class	TBMR	Class implementing the Tree Based Morse Regions (TBMR) as described in CITE: Najman2014 extended with scaled extraction ability.
class	VGG	Class implementing VGG (Oxford Visual Geometry Group) descriptor trained end to end using "Descriptor Learning Using Convex Optimisation" (DLCO) aparatus described in CITE: Simonyan14.