Implementation of the Shape Context descriptor and matching algorithm. More...

#include <opencv2/shape/shape_distance.hpp>

Inheritance diagram for cv::ShapeContextDistanceExtractor:

Public Member Functions
virtual int	getAngularBins () const =0

virtual float	getBendingEnergyWeight () const =0

virtual Ptr < HistogramCostExtractor >	getCostExtractor () const =0

virtual float	getImageAppearanceWeight () const =0

virtual void	getImages (OutputArray image1, OutputArray image2) const =0

virtual float	getInnerRadius () const =0

virtual int	getIterations () const =0

virtual float	getOuterRadius () const =0

virtual int	getRadialBins () const =0

virtual bool	getRotationInvariant () const =0

virtual float	getShapeContextWeight () const =0

virtual float	getStdDev () const =0

virtual Ptr< ShapeTransformer >	getTransformAlgorithm () const =0

virtual void	setAngularBins (int nAngularBins)=0
	Establish the number of angular bins for the Shape Context Descriptor used in the shape matching pipeline.

virtual void	setBendingEnergyWeight (float bendingEnergyWeight)=0
	Set the weight of the Bending Energy in the final value of the shape distance. The bending energy definition depends on what transformation is being used to align the shapes. The final value of the shape distance is a user-defined linear combination of the shape context distance, an image appearance distance, and a bending energy.

virtual void	setCostExtractor (Ptr< HistogramCostExtractor > comparer)=0
	Set the algorithm used for building the shape context descriptor cost matrix.

virtual void	setImageAppearanceWeight (float imageAppearanceWeight)=0
	Set the weight of the Image Appearance cost in the final value of the shape distance. The image appearance cost is defined as the sum of squared brightness differences in Gaussian windows around corresponding image points. The final value of the shape distance is a user-defined linear combination of the shape context distance, an image appearance distance, and a bending energy. If this value is set to a number different from 0, is mandatory to set the images that correspond to each shape.

virtual void	setImages (InputArray image1, InputArray image2)=0
	Set the images that correspond to each shape. This images are used in the calculation of the Image Appearance cost.

virtual void	setInnerRadius (float innerRadius)=0
	Set the inner radius of the shape context descriptor.

virtual void	setIterations (int iterations)=0

virtual void	setOuterRadius (float outerRadius)=0
	Set the outer radius of the shape context descriptor.

virtual void	setRadialBins (int nRadialBins)=0
	Establish the number of radial bins for the Shape Context Descriptor used in the shape matching pipeline.

virtual void	setRotationInvariant (bool rotationInvariant)=0

virtual void	setShapeContextWeight (float shapeContextWeight)=0
	Set the weight of the shape context distance in the final value of the shape distance. The shape context distance between two shapes is defined as the symmetric sum of shape context matching costs over best matching points. The final value of the shape distance is a user-defined linear combination of the shape context distance, an image appearance distance, and a bending energy.

virtual void	setStdDev (float sigma)=0
	Set the value of the standard deviation for the Gaussian window for the image appearance cost.

virtual void	setTransformAlgorithm (Ptr< ShapeTransformer > transformer)=0
	Set the algorithm used for aligning the shapes.

Public Member Functions inherited from cv::ShapeDistanceExtractor
virtual float	computeDistance (InputArray contour1, InputArray contour2)=0
	Compute the shape distance between two shapes defined by its contours.

Public Member Functions inherited from cv::Algorithm
	Algorithm ()

virtual	~Algorithm ()

virtual void	clear ()
	Clears the algorithm state.

virtual bool	empty () const
	Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read.

virtual String	getDefaultName () const

virtual void	read (const FileNode &fn)
	Reads algorithm parameters from a file storage.

virtual void	save (const String &filename) const

virtual void	write (FileStorage &fs) const
	Stores algorithm parameters in a file storage.

void	write (const Ptr< FileStorage > &fs, const String &name=String()) const
	simplified API for language bindingsThis is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

Additional Inherited Members
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.

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

Detailed Description

Implementation of the Shape Context descriptor and matching algorithm.

proposed by Belongie et al. in "Shape Matching and Object Recognition Using Shape Contexts" (PAMI 2002). This implementation is packaged in a generic scheme, in order to allow you the implementation of the common variations of the original pipeline.

Member Function Documentation

virtual int cv::ShapeContextDistanceExtractor::getAngularBins ( ) const

pure virtual

Python:
	retval	=	cv.ShapeContextDistanceExtractor.getAngularBins(		)

virtual float cv::ShapeContextDistanceExtractor::getBendingEnergyWeight ( ) const

pure virtual

Python:
	retval	=	cv.ShapeContextDistanceExtractor.getBendingEnergyWeight(		)

virtual Ptr<HistogramCostExtractor> cv::ShapeContextDistanceExtractor::getCostExtractor ( ) const

pure virtual

Python:
	retval	=	cv.ShapeContextDistanceExtractor.getCostExtractor(		)

virtual float cv::ShapeContextDistanceExtractor::getImageAppearanceWeight ( ) const

pure virtual

Python:
	retval	=	cv.ShapeContextDistanceExtractor.getImageAppearanceWeight(		)

virtual void cv::ShapeContextDistanceExtractor::getImages	(	OutputArray	image1,
		OutputArray	image2
	)		const

pure virtual

Python:
	image1, image2	=	cv.ShapeContextDistanceExtractor.getImages(	[, image1[, image2]]	)

virtual float cv::ShapeContextDistanceExtractor::getInnerRadius ( ) const

pure virtual

Python:
	retval	=	cv.ShapeContextDistanceExtractor.getInnerRadius(		)

virtual int cv::ShapeContextDistanceExtractor::getIterations ( ) const

pure virtual

Python:
	retval	=	cv.ShapeContextDistanceExtractor.getIterations(		)

virtual float cv::ShapeContextDistanceExtractor::getOuterRadius ( ) const

pure virtual

Python:
	retval	=	cv.ShapeContextDistanceExtractor.getOuterRadius(		)

virtual int cv::ShapeContextDistanceExtractor::getRadialBins ( ) const

pure virtual

Python:
	retval	=	cv.ShapeContextDistanceExtractor.getRadialBins(		)

virtual bool cv::ShapeContextDistanceExtractor::getRotationInvariant ( ) const

pure virtual

Python:
	retval	=	cv.ShapeContextDistanceExtractor.getRotationInvariant(		)

virtual float cv::ShapeContextDistanceExtractor::getShapeContextWeight ( ) const

pure virtual

Python:
	retval	=	cv.ShapeContextDistanceExtractor.getShapeContextWeight(		)

virtual float cv::ShapeContextDistanceExtractor::getStdDev ( ) const

pure virtual

Python:
	retval	=	cv.ShapeContextDistanceExtractor.getStdDev(		)

virtual Ptr<ShapeTransformer> cv::ShapeContextDistanceExtractor::getTransformAlgorithm ( ) const

pure virtual

Python:
	retval	=	cv.ShapeContextDistanceExtractor.getTransformAlgorithm(		)

virtual void cv::ShapeContextDistanceExtractor::setAngularBins ( int nAngularBins )

pure virtual

Python:
	None	=	cv.ShapeContextDistanceExtractor.setAngularBins(	nAngularBins	)

Establish the number of angular bins for the Shape Context Descriptor used in the shape matching pipeline.

Parameters

nAngularBins The number of angular bins in the shape context descriptor.

virtual void cv::ShapeContextDistanceExtractor::setBendingEnergyWeight ( float bendingEnergyWeight )

pure virtual

Python:
	None	=	cv.ShapeContextDistanceExtractor.setBendingEnergyWeight(	bendingEnergyWeight	)

Set the weight of the Bending Energy in the final value of the shape distance. The bending energy definition depends on what transformation is being used to align the shapes. The final value of the shape distance is a user-defined linear combination of the shape context distance, an image appearance distance, and a bending energy.

Parameters

bendingEnergyWeight The weight of the Bending Energy in the final distance value.

virtual void cv::ShapeContextDistanceExtractor::setCostExtractor ( Ptr< HistogramCostExtractor > comparer )

pure virtual

Python:
	None	=	cv.ShapeContextDistanceExtractor.setCostExtractor(	comparer	)

Set the algorithm used for building the shape context descriptor cost matrix.

Parameters

comparer Smart pointer to a HistogramCostExtractor, an algorithm that defines the cost matrix between descriptors.

virtual void cv::ShapeContextDistanceExtractor::setImageAppearanceWeight ( float imageAppearanceWeight )

pure virtual

Python:
	None	=	cv.ShapeContextDistanceExtractor.setImageAppearanceWeight(	imageAppearanceWeight	)

Set the weight of the Image Appearance cost in the final value of the shape distance. The image appearance cost is defined as the sum of squared brightness differences in Gaussian windows around corresponding image points. The final value of the shape distance is a user-defined linear combination of the shape context distance, an image appearance distance, and a bending energy. If this value is set to a number different from 0, is mandatory to set the images that correspond to each shape.

Parameters

imageAppearanceWeight The weight of the appearance cost in the final distance value.

virtual void cv::ShapeContextDistanceExtractor::setImages	(	InputArray	image1,
		InputArray	image2
	)

pure virtual

Python:
	None	=	cv.ShapeContextDistanceExtractor.setImages(	image1, image2	)

Set the images that correspond to each shape. This images are used in the calculation of the Image Appearance cost.

Parameters

image1	Image corresponding to the shape defined by contours1.
image2	Image corresponding to the shape defined by contours2.

virtual void cv::ShapeContextDistanceExtractor::setInnerRadius ( float innerRadius )

pure virtual

Python:
	None	=	cv.ShapeContextDistanceExtractor.setInnerRadius(	innerRadius	)

Set the inner radius of the shape context descriptor.

Parameters

innerRadius The value of the inner radius.

virtual void cv::ShapeContextDistanceExtractor::setIterations ( int iterations )

pure virtual

Python:
	None	=	cv.ShapeContextDistanceExtractor.setIterations(	iterations	)

virtual void cv::ShapeContextDistanceExtractor::setOuterRadius ( float outerRadius )

pure virtual

Python:
	None	=	cv.ShapeContextDistanceExtractor.setOuterRadius(	outerRadius	)

Set the outer radius of the shape context descriptor.

Parameters

outerRadius The value of the outer radius.

virtual void cv::ShapeContextDistanceExtractor::setRadialBins ( int nRadialBins )

pure virtual

Python:
	None	=	cv.ShapeContextDistanceExtractor.setRadialBins(	nRadialBins	)

Establish the number of radial bins for the Shape Context Descriptor used in the shape matching pipeline.

Parameters

nRadialBins The number of radial bins in the shape context descriptor.

virtual void cv::ShapeContextDistanceExtractor::setRotationInvariant ( bool rotationInvariant )

pure virtual

Python:
	None	=	cv.ShapeContextDistanceExtractor.setRotationInvariant(	rotationInvariant	)

virtual void cv::ShapeContextDistanceExtractor::setShapeContextWeight ( float shapeContextWeight )

pure virtual

Python:
	None	=	cv.ShapeContextDistanceExtractor.setShapeContextWeight(	shapeContextWeight	)

Set the weight of the shape context distance in the final value of the shape distance. The shape context distance between two shapes is defined as the symmetric sum of shape context matching costs over best matching points. The final value of the shape distance is a user-defined linear combination of the shape context distance, an image appearance distance, and a bending energy.

Parameters

shapeContextWeight The weight of the shape context distance in the final distance value.

virtual void cv::ShapeContextDistanceExtractor::setStdDev ( float sigma )

pure virtual

Python:
	None	=	cv.ShapeContextDistanceExtractor.setStdDev(	sigma	)

Set the value of the standard deviation for the Gaussian window for the image appearance cost.

Parameters

sigma Standard Deviation.

virtual void cv::ShapeContextDistanceExtractor::setTransformAlgorithm ( Ptr< ShapeTransformer > transformer )

pure virtual

Python:
	None	=	cv.ShapeContextDistanceExtractor.setTransformAlgorithm(	transformer	)

Set the algorithm used for aligning the shapes.

Parameters

transformer Smart pointer to a ShapeTransformer, an algorithm that defines the aligning transformation.

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

shape_distance.hpp

Public Member Functions

Additional Inherited Members

Detailed Description

Member Function Documentation