Class cv::GeneralizedHough#

finds arbitrary template in the grayscale image using Generalized Hough Transform

#include <opencv2/imgproc.hpp>

Collaboration diagram for cv::GeneralizedHough:

Public Member Functions#

Public Member Functions inherited from cv::Algorithm

Return	Name	Description
	`Algorithm()`
	`~Algorithm()`
`void`	`clear()`	Clears the algorithm state.
`bool`	`empty()`	Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read.
`String`	`getDefaultName()`
`void`	`read(const FileNode & fn)`	Reads algorithm parameters from a file storage.
`void`	`save(const String & filename)`
`void`	`write(` `const Ptr< FileStorage > & fs,` `const String & name = String() )`
`void`	`write(FileStorage & fs)`	Stores algorithm parameters in a file storage.
`void`	`write(` `FileStorage & fs,` `const String & name )`

Static Public Member Functions#

Static Public Member Functions inherited from cv::Algorithm

Return	Name	Description
`static Ptr< _Tp >`	`load(` `const String & filename,` `const String & objname = String() )`	Loads algorithm from the file.
`static Ptr< _Tp >`	`loadFromString(` `const String & strModel,` `const String & objname = String() )`	Loads algorithm from a String.
`static Ptr< _Tp >`	`read(const FileNode & fn)`	Reads algorithm from the file node.

Additional Inherited Members#

Detailed Description#

finds arbitrary template in the grayscale image using Generalized Hough Transform

Member Function Documentation#

detect()#

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

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()#

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

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()#

int cv::GeneralizedHough::getCannyHighThresh()

Python:

cv.GeneralizedHough.getCannyHighThresh() -> retval

getCannyLowThresh()#

int cv::GeneralizedHough::getCannyLowThresh()

Python:

cv.GeneralizedHough.getCannyLowThresh() -> retval

getDp()#

double cv::GeneralizedHough::getDp()

Python:

cv.GeneralizedHough.getDp() -> retval

getMaxBufferSize()#

int cv::GeneralizedHough::getMaxBufferSize()

Python:

cv.GeneralizedHough.getMaxBufferSize() -> retval

getMinDist()#

double cv::GeneralizedHough::getMinDist()

Python:

cv.GeneralizedHough.getMinDist() -> retval

setCannyHighThresh()#

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

Python:

cv.GeneralizedHough.setCannyHighThresh(cannyHighThresh)

Canny high threshold.

setCannyLowThresh()#

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

Python:

cv.GeneralizedHough.setCannyLowThresh(cannyLowThresh)

Canny low threshold.

setDp()#

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

Python:

cv.GeneralizedHough.setDp(dp)

Inverse ratio of the accumulator resolution to the image resolution.

setMaxBufferSize()#

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

Python:

cv.GeneralizedHough.setMaxBufferSize(maxBufferSize)

Maximal size of inner buffers.

setMinDist()#

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

Python:

cv.GeneralizedHough.setMinDist(minDist)

Minimum distance between the centers of the detected objects.

setTemplate()#

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

Python:

cv.GeneralizedHough.setTemplate(templ[, templCenter])

cv.GeneralizedHough.setTemplate(edges, dx, dy[, templCenter])

setTemplate()#

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

Python:

cv.GeneralizedHough.setTemplate(templ[, templCenter])

cv.GeneralizedHough.setTemplate(edges, dx, dy[, templCenter])

set template to search

Source file#

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

opencv2/imgproc.hpp