class cv::GeneralizedHoughBallard
Overview
Ballard, D.H. Moreā¦
#include <imgproc.hpp> class GeneralizedHoughBallard: public cv::GeneralizedHough { public: // methods virtual int getLevels() const = 0; virtual int getVotesThreshold() const = 0; virtual void setLevels(int levels) = 0; virtual void setVotesThreshold(int votesThreshold) = 0; };
Inherited Members
public: // methods virtual void clear(); virtual bool empty() const; virtual String getDefaultName() const; virtual void read(const FileNode& fn); virtual void save(const String& filename) const; virtual void write(FileStorage& fs) const; template <typename _Tp> static Ptr<_Tp> load( const String& filename, const String& objname = String() ); template <typename _Tp> static Ptr<_Tp> loadFromString( const String& strModel, const String& objname = String() ); template <typename _Tp> static Ptr<_Tp> read(const FileNode& fn); virtual void detect( InputArray image, OutputArray positions, OutputArray votes = noArray() ) = 0; 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; virtual void setCannyLowThresh(int cannyLowThresh) = 0; virtual void setDp(double dp) = 0; virtual void setMaxBufferSize(int maxBufferSize) = 0; virtual void setMinDist(double minDist) = 0; virtual void setTemplate( InputArray templ, Point templCenter = Point(-1, -1) ) = 0; virtual void setTemplate( InputArray edges, InputArray dx, InputArray dy, Point templCenter = Point(-1, -1) ) = 0; protected: // methods void writeFormat(FileStorage& fs) const;
Detailed Documentation
Ballard, D.H. (1981). Generalizing the Hough transform to detect arbitrary shapes. Pattern Recognition 13 (2): 111-122. Detects position only without translation and rotation
Methods
virtual void setLevels(int levels) = 0
R-Table levels.
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.