Uses of Class
org.opencv.core.Algorithm

Packages that use Algorithm

Package	Description
org.opencv.bgsegm
org.opencv.bioinspired
org.opencv.calib3d
org.opencv.core
org.opencv.dnn
org.opencv.face
org.opencv.features2d
org.opencv.img_hash
org.opencv.imgproc
org.opencv.ml
org.opencv.objdetect
org.opencv.phase_unwrapping
org.opencv.photo
org.opencv.plot
org.opencv.structured_light
org.opencv.text
org.opencv.tracking
org.opencv.video
org.opencv.xfeatures2d
org.opencv.ximgproc
org.opencv.xphoto

Uses of Algorithm in org.opencv.bgsegm

Subclasses of Algorithm in org.opencv.bgsegm

Modifier and Type	Class	Description
class	BackgroundSubtractorCNT	Background subtraction based on counting.
class	BackgroundSubtractorGMG	Background Subtractor module based on the algorithm given in CITE: Gold2012 .
class	BackgroundSubtractorGSOC	Implementation of the different yet better algorithm which is called GSOC, as it was implemented during GSOC and was not originated from any paper.
class	BackgroundSubtractorLSBP	Background Subtraction using Local SVD Binary Pattern.
class	BackgroundSubtractorMOG	Gaussian Mixture-based Background/Foreground Segmentation Algorithm.
class	SyntheticSequenceGenerator	Synthetic frame sequence generator for testing background subtraction algorithms.

Uses of Algorithm in org.opencv.bioinspired

Subclasses of Algorithm in org.opencv.bioinspired

Modifier and Type	Class	Description
class	Retina	class which allows the Gipsa/Listic Labs model to be used with OpenCV.
class	RetinaFastToneMapping	a wrapper class which allows the tone mapping algorithm of Meylan&al(2007) to be used with OpenCV.
class	TransientAreasSegmentationModule	class which provides a transient/moving areas segmentation module perform a locally adapted segmentation by using the retina magno input data Based on Alexandre BENOIT thesis: "Le système visuel humain au secours de la vision par ordinateur" 3 spatio temporal filters are used: a first one which filters the noise and local variations of the input motion energy a second (more powerfull low pass spatial filter) which gives the neighborhood motion energy the segmentation consists in the comparison of these both outputs, if the local motion energy is higher to the neighborhood otion energy, then the area is considered as moving and is segmented a stronger third low pass filter helps decision by providing a smooth information about the "motion context" in a wider area

Uses of Algorithm in org.opencv.calib3d

Subclasses of Algorithm in org.opencv.calib3d

Modifier and Type	Class	Description
class	StereoBM	Class for computing stereo correspondence using the block matching algorithm, introduced and contributed to OpenCV by K.
class	StereoMatcher	The base class for stereo correspondence algorithms.
class	StereoSGBM	The class implements the modified H.

Uses of Algorithm in org.opencv.core

Methods in org.opencv.core that return Algorithm

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

Uses of Algorithm in org.opencv.dnn

Subclasses of Algorithm in org.opencv.dnn

Modifier and Type	Class	Description
class	Layer	This interface class allows to build new Layers - are building blocks of networks.

Uses of Algorithm in org.opencv.face

Subclasses of Algorithm in org.opencv.face

Modifier and Type	Class	Description
class	BasicFaceRecognizer
class	BIF	Implementation of bio-inspired features (BIF) from the paper: Guo, Guodong, et al.
class	EigenFaceRecognizer
class	Facemark	Abstract base class for all facemark models To utilize this API in your program, please take a look at the REF: tutorial_table_of_content_facemark ### Description Facemark is a base class which provides universal access to any specific facemark algorithm.
class	FacemarkAAM
class	FacemarkKazemi
class	FacemarkLBF
class	FacemarkTrain	Abstract base class for trainable facemark models To utilize this API in your program, please take a look at the REF: tutorial_table_of_content_facemark ### Description The AAM and LBF facemark models in OpenCV are derived from the abstract base class FacemarkTrain, which provides a unified access to those facemark algorithms in OpenCV.
class	FaceRecognizer	Abstract base class for all face recognition models All face recognition models in OpenCV are derived from the abstract base class FaceRecognizer, which provides a unified access to all face recongition algorithms in OpenCV.
class	FisherFaceRecognizer
class	LBPHFaceRecognizer
class	MACE	Minimum Average Correlation Energy Filter useful for authentication with (cancellable) biometrical features.

Uses of Algorithm in org.opencv.features2d

Subclasses of Algorithm 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	BFMatcher	Brute-force descriptor matcher.
class	BRISK	Class implementing the BRISK keypoint detector and descriptor extractor, described in CITE: LCS11 .
class	DescriptorMatcher	Abstract base class for matching keypoint descriptors.
class	FastFeatureDetector	Wrapping class for feature detection using the FAST method.
class	Feature2D	Abstract base class for 2D image feature detectors and descriptor extractors
class	FlannBasedMatcher	Flann-based descriptor matcher.
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.

Uses of Algorithm in org.opencv.img_hash

Subclasses of Algorithm in org.opencv.img_hash

Modifier and Type	Class	Description
class	AverageHash	Computes average hash value of the input image This is a fast image hashing algorithm, but only work on simple case.
class	BlockMeanHash	Image hash based on block mean.
class	ColorMomentHash	Image hash based on color moments.
class	ImgHashBase	The base class for image hash algorithms
class	MarrHildrethHash	Marr-Hildreth Operator Based Hash, slowest but more discriminative.
class	PHash	pHash Slower than average_hash, but tolerant of minor modifications This algorithm can combat more variation than averageHash, for more details please refer to CITE: lookslikeit
class	RadialVarianceHash	Image hash based on Radon transform.

Uses of Algorithm in org.opencv.imgproc

Subclasses of Algorithm in org.opencv.imgproc

Modifier and Type	Class	Description
class	CLAHE	Base class for Contrast Limited Adaptive Histogram Equalization.
class	GeneralizedHough	finds arbitrary template in the grayscale image using Generalized Hough Transform
class	GeneralizedHoughBallard	finds arbitrary template in the grayscale image using Generalized Hough Transform Detects position only without translation and rotation CITE: Ballard1981 .
class	GeneralizedHoughGuil	finds arbitrary template in the grayscale image using Generalized Hough Transform Detects position, translation and rotation CITE: Guil1999 .
class	LineSegmentDetector	Line segment detector class following the algorithm described at CITE: Rafael12 .

Uses of Algorithm in org.opencv.ml

Subclasses of Algorithm in org.opencv.ml

Modifier and Type	Class	Description
class	ANN_MLP	Artificial Neural Networks - Multi-Layer Perceptrons.
class	Boost	Boosted tree classifier derived from DTrees SEE: REF: ml_intro_boost
class	DTrees	The class represents a single decision tree or a collection of decision trees.
class	EM	The class implements the Expectation Maximization algorithm.
class	KNearest	The class implements K-Nearest Neighbors model SEE: REF: ml_intro_knn
class	LogisticRegression	Implements Logistic Regression classifier.
class	NormalBayesClassifier	Bayes classifier for normally distributed data.
class	RTrees	The class implements the random forest predictor.
class	StatModel	Base class for statistical models in OpenCV ML.
class	SVM	Support Vector Machines.
class	SVMSGD	*************************************************************************************\ Stochastic Gradient Descent SVM Classifier * \***************************************************************************************

Uses of Algorithm in org.opencv.objdetect

Subclasses of Algorithm in org.opencv.objdetect

Modifier and Type	Class	Description
class	BaseCascadeClassifier

Uses of Algorithm in org.opencv.phase_unwrapping

Subclasses of Algorithm in org.opencv.phase_unwrapping

Modifier and Type	Class	Description
class	HistogramPhaseUnwrapping	Class implementing two-dimensional phase unwrapping based on CITE: histogramUnwrapping This algorithm belongs to the quality-guided phase unwrapping methods.
class	PhaseUnwrapping	Abstract base class for phase unwrapping.

Uses of Algorithm in org.opencv.photo

Subclasses of Algorithm in org.opencv.photo

Modifier and Type	Class	Description
class	AlignExposures	The base class for algorithms that align images of the same scene with different exposures
class	AlignMTB	This algorithm converts images to median threshold bitmaps (1 for pixels brighter than median luminance and 0 otherwise) and than aligns the resulting bitmaps using bit operations.
class	CalibrateCRF	The base class for camera response calibration algorithms.
class	CalibrateDebevec	Inverse camera response function is extracted for each brightness value by minimizing an objective function as linear system.
class	CalibrateRobertson	Inverse camera response function is extracted for each brightness value by minimizing an objective function as linear system.
class	MergeDebevec	The resulting HDR image is calculated as weighted average of the exposures considering exposure values and camera response.
class	MergeExposures	The base class algorithms that can merge exposure sequence to a single image.
class	MergeMertens	Pixels are weighted using contrast, saturation and well-exposedness measures, than images are combined using laplacian pyramids.
class	MergeRobertson	The resulting HDR image is calculated as weighted average of the exposures considering exposure values and camera response.
class	Tonemap	Base class for tonemapping algorithms - tools that are used to map HDR image to 8-bit range.
class	TonemapDrago	Adaptive logarithmic mapping is a fast global tonemapping algorithm that scales the image in logarithmic domain.
class	TonemapMantiuk	This algorithm transforms image to contrast using gradients on all levels of gaussian pyramid, transforms contrast values to HVS response and scales the response.
class	TonemapReinhard	This is a global tonemapping operator that models human visual system.

Uses of Algorithm in org.opencv.plot

Subclasses of Algorithm in org.opencv.plot

Modifier and Type	Class	Description
class	Plot2d	plot Plot function for Mat data

Uses of Algorithm in org.opencv.structured_light

Subclasses of Algorithm in org.opencv.structured_light

Modifier and Type	Class	Description
class	GrayCodePattern	Class implementing the Gray-code pattern, based on CITE: UNDERWORLD.
class	SinusoidalPattern	Class implementing Fourier transform profilometry (FTP) , phase-shifting profilometry (PSP) and Fourier-assisted phase-shifting profilometry (FAPS) based on CITE: faps.
class	StructuredLightPattern	Abstract base class for generating and decoding structured light patterns.

Uses of Algorithm in org.opencv.text

Subclasses of Algorithm in org.opencv.text

Modifier and Type	Class	Description
class	ERFilter	Base class for 1st and 2nd stages of Neumann and Matas scene text detection algorithm CITE: Neumann12.

Uses of Algorithm in org.opencv.tracking

Subclasses of Algorithm in org.opencv.tracking

Modifier and Type	Class	Description
class	legacy_MultiTracker	This class is used to track multiple objects using the specified tracker algorithm.
class	legacy_Tracker	Base abstract class for the long-term tracker:
class	legacy_TrackerBoosting	the Boosting tracker This is a real-time object tracking based on a novel on-line version of the AdaBoost algorithm.
class	legacy_TrackerCSRT	the CSRT tracker The implementation is based on CITE: Lukezic_IJCV2018 Discriminative Correlation Filter with Channel and Spatial Reliability
class	legacy_TrackerKCF	the KCF (Kernelized Correlation Filter) tracker KCF is a novel tracking framework that utilizes properties of circulant matrix to enhance the processing speed.
class	legacy_TrackerMedianFlow	the Median Flow tracker Implementation of a paper CITE: MedianFlow .
class	legacy_TrackerMIL	The MIL algorithm trains a classifier in an online manner to separate the object from the background.
class	legacy_TrackerMOSSE	the MOSSE (Minimum Output Sum of Squared %Error) tracker The implementation is based on CITE: MOSSE Visual Object Tracking using Adaptive Correlation Filters Note: this tracker works with grayscale images, if passed bgr ones, they will get converted internally.
class	legacy_TrackerTLD	the TLD (Tracking, learning and detection) tracker TLD is a novel tracking framework that explicitly decomposes the long-term tracking task into tracking, learning and detection.

Uses of Algorithm in org.opencv.video

Subclasses of Algorithm in org.opencv.video

Modifier and Type	Class	Description
class	BackgroundSubtractor	Base class for background/foreground segmentation.
class	BackgroundSubtractorKNN	K-nearest neighbours - based Background/Foreground Segmentation Algorithm.
class	BackgroundSubtractorMOG2	Gaussian Mixture-based Background/Foreground Segmentation Algorithm.
class	DenseOpticalFlow	Base class for dense optical flow algorithms
class	DISOpticalFlow	DIS optical flow algorithm.
class	FarnebackOpticalFlow	Class computing a dense optical flow using the Gunnar Farneback's algorithm.
class	SparseOpticalFlow	Base interface for sparse optical flow algorithms.
class	SparsePyrLKOpticalFlow	Class used for calculating a sparse optical flow.
class	VariationalRefinement	Variational optical flow refinement This class implements variational refinement of the input flow field, i.e.

Uses of Algorithm in org.opencv.xfeatures2d

Subclasses of Algorithm 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	PCTSignatures	Class implementing PCT (position-color-texture) signature extraction as described in CITE: KrulisLS16.
class	PCTSignaturesSQFD	Class implementing Signature Quadratic Form Distance (SQFD).
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.

Uses of Algorithm in org.opencv.ximgproc

Subclasses of Algorithm in org.opencv.ximgproc

Modifier and Type	Class	Description
class	AdaptiveManifoldFilter	Interface for Adaptive Manifold Filter realizations.
class	ContourFitting	Class for ContourFitting algorithms.
class	DisparityFilter	Main interface for all disparity map filters.
class	DisparityWLSFilter	Disparity map filter based on Weighted Least Squares filter (in form of Fast Global Smoother that is a lot faster than traditional Weighted Least Squares filter implementations) and optional use of left-right-consistency-based confidence to refine the results in half-occlusions and uniform areas.
class	DTFilter	Interface for realizations of Domain Transform filter.
class	EdgeAwareInterpolator	Sparse match interpolation algorithm based on modified locally-weighted affine estimator from CITE: Revaud2015 and Fast Global Smoother as post-processing filter.
class	EdgeBoxes	Class implementing EdgeBoxes algorithm from CITE: ZitnickECCV14edgeBoxes :
class	EdgeDrawing	Class implementing the ED (EdgeDrawing) CITE: topal2012edge, EDLines CITE: akinlar2011edlines, EDPF CITE: akinlar2012edpf and EDCircles CITE: akinlar2013edcircles algorithms
class	FastBilateralSolverFilter	Interface for implementations of Fast Bilateral Solver.
class	FastGlobalSmootherFilter	Interface for implementations of Fast Global Smoother filter.
class	FastLineDetector	Class implementing the FLD (Fast Line Detector) algorithm described in CITE: Lee14 .
class	GraphSegmentation	Graph Based Segmentation Algorithm.
class	GuidedFilter	Interface for realizations of Guided Filter.
class	RFFeatureGetter	Jun 17, 2014
class	RICInterpolator	Sparse match interpolation algorithm based on modified piecewise locally-weighted affine estimator called Robust Interpolation method of Correspondences or RIC from CITE: Hu2017 and Variational and Fast Global Smoother as post-processing filter.
class	RidgeDetectionFilter	Applies Ridge Detection Filter to an input image.
class	SelectiveSearchSegmentation	Selective search segmentation algorithm The class implements the algorithm described in CITE: uijlings2013selective.
class	SelectiveSearchSegmentationStrategy	Strategie for the selective search segmentation algorithm The class implements a generic stragery for the algorithm described in CITE: uijlings2013selective.
class	SelectiveSearchSegmentationStrategyColor	Color-based strategy for the selective search segmentation algorithm The class is implemented from the algorithm described in CITE: uijlings2013selective.
class	SelectiveSearchSegmentationStrategyFill	Fill-based strategy for the selective search segmentation algorithm The class is implemented from the algorithm described in CITE: uijlings2013selective.
class	SelectiveSearchSegmentationStrategyMultiple	Regroup multiple strategies for the selective search segmentation algorithm
class	SelectiveSearchSegmentationStrategySize	Size-based strategy for the selective search segmentation algorithm The class is implemented from the algorithm described in CITE: uijlings2013selective.
class	SelectiveSearchSegmentationStrategyTexture	Texture-based strategy for the selective search segmentation algorithm The class is implemented from the algorithm described in CITE: uijlings2013selective.
class	SparseMatchInterpolator	Main interface for all filters, that take sparse matches as an input and produce a dense per-pixel matching (optical flow) as an output.
class	StructuredEdgeDetection	Class implementing edge detection algorithm from CITE: Dollar2013 :
class	SuperpixelLSC	Class implementing the LSC (Linear Spectral Clustering) superpixels algorithm described in CITE: LiCVPR2015LSC.
class	SuperpixelSEEDS	Class implementing the SEEDS (Superpixels Extracted via Energy-Driven Sampling) superpixels algorithm described in CITE: VBRV14 .
class	SuperpixelSLIC	Class implementing the SLIC (Simple Linear Iterative Clustering) superpixels algorithm described in CITE: Achanta2012.

Uses of Algorithm in org.opencv.xphoto

Subclasses of Algorithm in org.opencv.xphoto

Modifier and Type	Class	Description
class	GrayworldWB	Gray-world white balance algorithm This algorithm scales the values of pixels based on a gray-world assumption which states that the average of all channels should result in a gray image.
class	LearningBasedWB	More sophisticated learning-based automatic white balance algorithm.
class	SimpleWB	A simple white balance algorithm that works by independently stretching each of the input image channels to the specified range.
class	TonemapDurand	This algorithm decomposes image into two layers: base layer and detail layer using bilateral filter and compresses contrast of the base layer thus preserving all the details.
class	WhiteBalancer	The base class for auto white balance algorithms.