Shape Distance and Matching

Detailed Description

Classes
class	cv::AffineTransformer
	Wrapper class for the OpenCV Affine Transformation algorithm. : More...
class	cv::ChiHistogramCostExtractor
	An Chi based cost extraction. : More...
class	cv::EMDHistogramCostExtractor
	An EMD based cost extraction. : More...
class	cv::EMDL1HistogramCostExtractor
	An EMD-L1 based cost extraction. : More...
class	cv::HausdorffDistanceExtractor
	A simple Hausdorff distance measure between shapes defined by contours. More...
class	cv::HistogramCostExtractor
	Abstract base class for histogram cost algorithms. More...
class	cv::NormHistogramCostExtractor
	A norm based cost extraction. : More...
class	cv::ShapeContextDistanceExtractor
	Implementation of the Shape Context descriptor and matching algorithm. More...
class	cv::ShapeDistanceExtractor
	Abstract base class for shape distance algorithms. More...
class	cv::ShapeTransformer
	Abstract base class for shape transformation algorithms. More...
class	cv::ThinPlateSplineShapeTransformer
	Definition of the transformation. More...

Functions
Ptr< AffineTransformer >	cv::createAffineTransformer (bool fullAffine)
Ptr< HistogramCostExtractor >	cv::createChiHistogramCostExtractor (int nDummies=25, float defaultCost=0.2f)
Ptr< HistogramCostExtractor >	cv::createEMDHistogramCostExtractor (int flag=DIST_L2, int nDummies=25, float defaultCost=0.2f)
Ptr< HistogramCostExtractor >	cv::createEMDL1HistogramCostExtractor (int nDummies=25, float defaultCost=0.2f)
Ptr< HausdorffDistanceExtractor >	cv::createHausdorffDistanceExtractor (int distanceFlag=cv::NORM_L2, float rankProp=0.6f)
Ptr< HistogramCostExtractor >	cv::createNormHistogramCostExtractor (int flag=DIST_L2, int nDummies=25, float defaultCost=0.2f)
Ptr< ShapeContextDistanceExtractor >	cv::createShapeContextDistanceExtractor (int nAngularBins=12, int nRadialBins=4, float innerRadius=0.2f, float outerRadius=2, int iterations=3, const Ptr< HistogramCostExtractor > &comparer=createChiHistogramCostExtractor(), const Ptr< ShapeTransformer > &transformer=createThinPlateSplineShapeTransformer())
Ptr< ThinPlateSplineShapeTransformer >	cv::createThinPlateSplineShapeTransformer (double regularizationParameter=0)
float	cv::EMDL1 (InputArray signature1, InputArray signature2)
	Computes the "minimal work" distance between two weighted point configurations base on the papers "EMD-L1: An efficient and Robust Algorithm for comparing histogram-based descriptors", by Haibin Ling and Kazunori Okuda; and "The Earth Mover's Distance is the Mallows Distance: Some Insights from Statistics", by Elizaveta Levina and Peter Bickel.

Function Documentation

createAffineTransformer()

Ptr< AffineTransformer > cv::createAffineTransformer

(

bool

fullAffine

)

Python:
	cv.createAffineTransformer(	fullAffine	) ->	retval

#include <opencv2/shape/shape_transformer.hpp>

Complete constructor

createChiHistogramCostExtractor()

Ptr< HistogramCostExtractor > cv::createChiHistogramCostExtractor	(	int	nDummies = 25,
		float	defaultCost = 0.2f
	)

Python:
	cv.createChiHistogramCostExtractor(	[, nDummies[, defaultCost]]	) ->	retval

#include <opencv2/shape/hist_cost.hpp>

createEMDHistogramCostExtractor()

Ptr< HistogramCostExtractor > cv::createEMDHistogramCostExtractor	(	int	flag = DIST_L2,
		int	nDummies = 25,
		float	defaultCost = 0.2f
	)

Python:
	cv.createEMDHistogramCostExtractor(	[, flag[, nDummies[, defaultCost]]]	) ->	retval

#include <opencv2/shape/hist_cost.hpp>

createEMDL1HistogramCostExtractor()

Ptr< HistogramCostExtractor > cv::createEMDL1HistogramCostExtractor	(	int	nDummies = 25,
		float	defaultCost = 0.2f
	)

Python:
	cv.createEMDL1HistogramCostExtractor(	[, nDummies[, defaultCost]]	) ->	retval

#include <opencv2/shape/hist_cost.hpp>

createHausdorffDistanceExtractor()

Ptr< HausdorffDistanceExtractor > cv::createHausdorffDistanceExtractor	(	int	distanceFlag = cv::NORM_L2,
		float	rankProp = 0.6f
	)

Python:
	cv.createHausdorffDistanceExtractor(	[, distanceFlag[, rankProp]]	) ->	retval

#include <opencv2/shape/shape_distance.hpp>

createNormHistogramCostExtractor()

Ptr< HistogramCostExtractor > cv::createNormHistogramCostExtractor	(	int	flag = DIST_L2,
		int	nDummies = 25,
		float	defaultCost = 0.2f
	)

Python:
	cv.createNormHistogramCostExtractor(	[, flag[, nDummies[, defaultCost]]]	) ->	retval

#include <opencv2/shape/hist_cost.hpp>

createShapeContextDistanceExtractor()

Ptr< ShapeContextDistanceExtractor > cv::createShapeContextDistanceExtractor	(	int	nAngularBins = 12,
		int	nRadialBins = 4,
		float	innerRadius = 0.2f,
		float	outerRadius = 2,
		int	iterations = 3,
		const Ptr< HistogramCostExtractor > &	comparer = createChiHistogramCostExtractor(),
		const Ptr< ShapeTransformer > &	transformer = createThinPlateSplineShapeTransformer()
	)

Python:
	cv.createShapeContextDistanceExtractor(	[, nAngularBins[, nRadialBins[, innerRadius[, outerRadius[, iterations[, comparer[, transformer]]]]]]]	) ->	retval

#include <opencv2/shape/shape_distance.hpp>

Examples

modules/shape/samples/shape_example.cpp.

createThinPlateSplineShapeTransformer()

Ptr< ThinPlateSplineShapeTransformer > cv::createThinPlateSplineShapeTransformer

(

double

regularizationParameter = 0

)

Python:
	cv.createThinPlateSplineShapeTransformer(	[, regularizationParameter]	) ->	retval

#include <opencv2/shape/shape_transformer.hpp>

Complete constructor

EMDL1()

float cv::EMDL1	(	InputArray	signature1,
		InputArray	signature2
	)

#include <opencv2/shape/emdL1.hpp>

Computes the "minimal work" distance between two weighted point configurations base on the papers "EMD-L1: An efficient and Robust Algorithm for comparing histogram-based descriptors", by Haibin Ling and Kazunori Okuda; and "The Earth Mover's Distance is the Mallows Distance: Some Insights from Statistics", by Elizaveta Levina and Peter Bickel.

Parameters

signature1	First signature, a single column floating-point matrix. Each row is the value of the histogram in each bin.
signature2	Second signature of the same format and size as signature1.