形状距离和匹配


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

函数

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. 更多...

详细描述

函数文档编制

createAffineTransformer()

Ptr < AffineTransformer > cv::createAffineTransformer ( bool fullAffine )
Python:
retval = cv.createAffineTransformer( fullAffine )

#include < opencv2/shape/shape_transformer.hpp >

Complete constructor

createChiHistogramCostExtractor()

Ptr < HistogramCostExtractor > cv::createChiHistogramCostExtractor ( int nDummies = 25 ,
float defaultCost = 0.2f
)
Python:
retval = cv.createChiHistogramCostExtractor( [, nDummies[, defaultCost]] )

createEMDHistogramCostExtractor()

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

createEMDL1HistogramCostExtractor()

Ptr < HistogramCostExtractor > cv::createEMDL1HistogramCostExtractor ( int nDummies = 25 ,
float defaultCost = 0.2f
)
Python:
retval = cv.createEMDL1HistogramCostExtractor( [, nDummies[, defaultCost]] )

createHausdorffDistanceExtractor()

Ptr < HausdorffDistanceExtractor > cv::createHausdorffDistanceExtractor ( int distanceFlag = cv::NORM_L2 ,
float rankProp = 0.6f
)
Python:
retval = cv.createHausdorffDistanceExtractor( [, distanceFlag[, rankProp]] )

createNormHistogramCostExtractor()

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

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

createThinPlateSplineShapeTransformer()

Ptr < ThinPlateSplineShapeTransformer > cv::createThinPlateSplineShapeTransformer ( double regularizationParameter = 0 )
Python:
retval = cv.createThinPlateSplineShapeTransformer( [, regularizationParameter] )

#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.