cv::GeneralizedHoughBallard Class Reference

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

#include "imgproc.hpp"

Inheritance diagram for cv::GeneralizedHoughBallard:

Public Member Functions
virtual int	getLevels () const =0
virtual int	getVotesThreshold () const =0
virtual void	setLevels (int levels)=0
	R-Table levels. More...
virtual void	setVotesThreshold (int votesThreshold)=0
	The accumulator threshold for the template centers at the detection stage. The smaller it is, the more false positions may be detected. More...
Public Member Functions inherited from cv::GeneralizedHough
virtual void	detect (InputArray image, OutputArray positions, OutputArray votes=noArray())=0
	find template on image More...
virtual void	detect (InputArray edges, InputArray dx, InputArray dy, OutputArray positions, OutputArray votes=noArray())=0
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. More...
virtual void	setCannyLowThresh (int cannyLowThresh)=0
	Canny low threshold. More...
virtual void	setDp (double dp)=0
	Inverse ratio of the accumulator resolution to the image resolution. More...
virtual void	setMaxBufferSize (int maxBufferSize)=0
	Maximal size of inner buffers. More...
virtual void	setMinDist (double minDist)=0
	Minimum distance between the centers of the detected objects. More...
virtual void	setTemplate (InputArray templ, Point templCenter=Point(-1, -1))=0
	set template to search More...
virtual void	setTemplate (InputArray edges, InputArray dx, InputArray dy, Point templCenter=Point(-1, -1))=0
Public Member Functions inherited from cv::Algorithm
	Algorithm ()
virtual	~Algorithm ()
virtual void	clear ()
	Clears the algorithm state. More...
virtual bool	empty () const
	Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read. More...
virtual String	getDefaultName () const
virtual void	read (const FileNode &fn)
	Reads algorithm parameters from a file storage. More...
virtual void	save (const String &filename) const
virtual void	write (FileStorage &fs) const
	Stores algorithm parameters in a file storage. More...
void	write (const Ptr< FileStorage > &fs, const String &name=String()) const
	simplified API for language bindings This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts. More...

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. More...
template<typename _Tp >
static Ptr< _Tp >	loadFromString (const String &strModel, const String &objname=String())
	Loads algorithm from a String. More...
template<typename _Tp >
static Ptr< _Tp >	read (const FileNode &fn)
	Reads algorithm from the file node. More...
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

Detects position only without translation and rotation [9] .

Member Function Documentation

getLevels()

virtual int cv::GeneralizedHoughBallard::getLevels ( ) const

pure virtual

Python:
	retval	=	cv.GeneralizedHoughBallard.getLevels(		)

getVotesThreshold()

virtual int cv::GeneralizedHoughBallard::getVotesThreshold ( ) const

pure virtual

Python:
	retval	=	cv.GeneralizedHoughBallard.getVotesThreshold(		)

setLevels()

virtual void cv::GeneralizedHoughBallard::setLevels ( int  levels )

pure virtual

Python:
	None	=	cv.GeneralizedHoughBallard.setLevels(	levels	)

R-Table levels.

setVotesThreshold()

virtual void cv::GeneralizedHoughBallard::setVotesThreshold ( int  votesThreshold )

pure virtual

Python:
	None	=	cv.GeneralizedHoughBallard.setVotesThreshold(	votesThreshold	)

The accumulator threshold for the template centers at the detection stage. The smaller it is, the more false positions may be detected.

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

• imgproc/include/opencv2/imgproc.hpp