cv::GeneralizedHough Class Reference

finds arbitrary template in the grayscale image using Generalized Hough Transform More...

#include <opencv2/imgproc.hpp>

Collaboration diagram for cv::GeneralizedHough:

Public Member Functions
virtual void	detect (InputArray edges, InputArray dx, InputArray dy, OutputArray positions, OutputArray votes=noArray())=0
virtual void	detect (InputArray image, OutputArray positions, OutputArray votes=noArray())=0
	find template on image
virtual int	getCannyHighThresh () const =0
virtual int	getCannyLowThresh () const =0
virtual double	getDp () const =0
virtual int	getMaxBufferSize () const =0
virtual double	getMinDist () const =0
virtual void	setCannyHighThresh (int cannyHighThresh)=0
	Canny high threshold.
virtual void	setCannyLowThresh (int cannyLowThresh)=0
	Canny low threshold.
virtual void	setDp (double dp)=0
	Inverse ratio of the accumulator resolution to the image resolution.
virtual void	setMaxBufferSize (int maxBufferSize)=0
	Maximal size of inner buffers.
virtual void	setMinDist (double minDist)=0
	Minimum distance between the centers of the detected objects.
virtual void	setTemplate (InputArray edges, InputArray dx, InputArray dy, Point templCenter=Point(-1, -1))=0
virtual void	setTemplate (InputArray templ, Point templCenter=Point(-1, -1))=0
	set template to search
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 (FileStorage &fs, const String &name) const

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

finds arbitrary template in the grayscale image using Generalized Hough Transform

Member Function Documentation

detect() [1/2]

virtual void cv::GeneralizedHough::detect ( InputArray edges, InputArray dx, InputArray dy, OutputArray positions, OutputArray votes = noArray() )

pure virtual

Python:
	cv.GeneralizedHough.detect(	image[, positions[, votes]]	) ->	positions, votes
	cv.GeneralizedHough.detect(	edges, dx, dy[, positions[, votes]]	) ->	positions, votes

Here is the call graph for this function:

detect() [2/2]

virtual void cv::GeneralizedHough::detect ( InputArray image, OutputArray positions, OutputArray votes = noArray() )

pure virtual

Python:
	cv.GeneralizedHough.detect(	image[, positions[, votes]]	) ->	positions, votes
	cv.GeneralizedHough.detect(	edges, dx, dy[, positions[, votes]]	) ->	positions, votes

find template on image

Here is the call graph for this function:

getCannyHighThresh()

virtual int cv::GeneralizedHough::getCannyHighThresh ( ) const

pure virtual

Python:
	cv.GeneralizedHough.getCannyHighThresh(		) ->	retval

getCannyLowThresh()

virtual int cv::GeneralizedHough::getCannyLowThresh ( ) const

pure virtual

Python:
	cv.GeneralizedHough.getCannyLowThresh(		) ->	retval

getDp()

virtual double cv::GeneralizedHough::getDp ( ) const

pure virtual

Python:
	cv.GeneralizedHough.getDp(		) ->	retval

getMaxBufferSize()

virtual int cv::GeneralizedHough::getMaxBufferSize ( ) const

pure virtual

Python:
	cv.GeneralizedHough.getMaxBufferSize(		) ->	retval

getMinDist()

virtual double cv::GeneralizedHough::getMinDist ( ) const

pure virtual

Python:
	cv.GeneralizedHough.getMinDist(		) ->	retval

setCannyHighThresh()

virtual void cv::GeneralizedHough::setCannyHighThresh ( int cannyHighThresh )

pure virtual

Python:
	cv.GeneralizedHough.setCannyHighThresh(	cannyHighThresh	) ->	None

Canny high threshold.

setCannyLowThresh()

virtual void cv::GeneralizedHough::setCannyLowThresh ( int cannyLowThresh )

pure virtual

Python:
	cv.GeneralizedHough.setCannyLowThresh(	cannyLowThresh	) ->	None

Canny low threshold.

setDp()

virtual void cv::GeneralizedHough::setDp ( double dp )

pure virtual

Python:
	cv.GeneralizedHough.setDp(	dp	) ->	None

Inverse ratio of the accumulator resolution to the image resolution.

setMaxBufferSize()

virtual void cv::GeneralizedHough::setMaxBufferSize ( int maxBufferSize )

pure virtual

Python:
	cv.GeneralizedHough.setMaxBufferSize(	maxBufferSize	) ->	None

Maximal size of inner buffers.

setMinDist()

virtual void cv::GeneralizedHough::setMinDist ( double minDist )

pure virtual

Python:
	cv.GeneralizedHough.setMinDist(	minDist	) ->	None

Minimum distance between the centers of the detected objects.

setTemplate() [1/2]

virtual void cv::GeneralizedHough::setTemplate ( InputArray edges, InputArray dx, InputArray dy, Point templCenter = Point(-1, -1) )

pure virtual

Python:
	cv.GeneralizedHough.setTemplate(	templ[, templCenter]	) ->	None
	cv.GeneralizedHough.setTemplate(	edges, dx, dy[, templCenter]	) ->	None

setTemplate() [2/2]

virtual void cv::GeneralizedHough::setTemplate ( InputArray templ, Point templCenter = Point(-1, -1) )

pure virtual

Python:
	cv.GeneralizedHough.setTemplate(	templ[, templCenter]	) ->	None
	cv.GeneralizedHough.setTemplate(	edges, dx, dy[, templCenter]	) ->	None

set template to search

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

• opencv2/imgproc.hpp