Hough Transform
===============
.. highlight:: cpp
cuda::HoughLinesDetector
------------------------
.. ocv:class:: cuda::HoughLinesDetector : public Algorithm
Base class for lines detector algorithm. ::
class CV_EXPORTS HoughLinesDetector : public Algorithm
{
public:
virtual void detect(InputArray src, OutputArray lines) = 0;
virtual void downloadResults(InputArray d_lines, OutputArray h_lines, OutputArray h_votes = noArray()) = 0;
virtual void setRho(float rho) = 0;
virtual float getRho() const = 0;
virtual void setTheta(float theta) = 0;
virtual float getTheta() const = 0;
virtual void setThreshold(int threshold) = 0;
virtual int getThreshold() const = 0;
virtual void setDoSort(bool doSort) = 0;
virtual bool getDoSort() const = 0;
virtual void setMaxLines(int maxLines) = 0;
virtual int getMaxLines() const = 0;
};
cuda::HoughLinesDetector::detect
--------------------------------
Finds lines in a binary image using the classical Hough transform.
.. ocv:function:: void cuda::HoughLinesDetector::detect(InputArray src, OutputArray lines)
:param src: 8-bit, single-channel binary source image.
:param lines: Output vector of lines. Each line is represented by a two-element vector :math:`(\rho, \theta)` . :math:`\rho` is the distance from the coordinate origin :math:`(0,0)` (top-left corner of the image). :math:`\theta` is the line rotation angle in radians ( :math:`0 \sim \textrm{vertical line}, \pi/2 \sim \textrm{horizontal line}` ).
.. seealso:: :ocv:func:`HoughLines`
cuda::HoughLinesDetector::downloadResults
-----------------------------------------
Downloads results from :ocv:func:`cuda::HoughLinesDetector::detect` to host memory.
.. ocv:function:: void cuda::HoughLinesDetector::downloadResults(InputArray d_lines, OutputArray h_lines, OutputArray h_votes = noArray())
:param d_lines: Result of :ocv:func:`cuda::HoughLinesDetector::detect` .
:param h_lines: Output host array.
:param h_votes: Optional output array for line's votes.
cuda::createHoughLinesDetector
------------------------------
Creates implementation for :ocv:class:`cuda::HoughLinesDetector` .
.. ocv:function:: Ptr<HoughLinesDetector> cuda::createHoughLinesDetector(float rho, float theta, int threshold, bool doSort = false, int maxLines = 4096)
:param rho: Distance resolution of the accumulator in pixels.
:param theta: Angle resolution of the accumulator in radians.
:param threshold: Accumulator threshold parameter. Only those lines are returned that get enough votes ( :math:`>\texttt{threshold}` ).
:param doSort: Performs lines sort by votes.
:param maxLines: Maximum number of output lines.
cuda::HoughSegmentDetector
--------------------------
.. ocv:class:: cuda::HoughSegmentDetector : public Algorithm
Base class for line segments detector algorithm. ::
class CV_EXPORTS HoughSegmentDetector : public Algorithm
{
public:
virtual void detect(InputArray src, OutputArray lines) = 0;
virtual void setRho(float rho) = 0;
virtual float getRho() const = 0;
virtual void setTheta(float theta) = 0;
virtual float getTheta() const = 0;
virtual void setMinLineLength(int minLineLength) = 0;
virtual int getMinLineLength() const = 0;
virtual void setMaxLineGap(int maxLineGap) = 0;
virtual int getMaxLineGap() const = 0;
virtual void setMaxLines(int maxLines) = 0;
virtual int getMaxLines() const = 0;
};
.. note::
* An example using the Hough segment detector can be found at opencv_source_code/samples/gpu/houghlines.cpp
cuda::HoughSegmentDetector::detect
----------------------------------
Finds line segments in a binary image using the probabilistic Hough transform.
.. ocv:function:: void cuda::HoughSegmentDetector::detect(InputArray src, OutputArray lines)
:param src: 8-bit, single-channel binary source image.
:param lines: Output vector of lines. Each line is represented by a 4-element vector :math:`(x_1, y_1, x_2, y_2)` , where :math:`(x_1,y_1)` and :math:`(x_2, y_2)` are the ending points of each detected line segment.
.. seealso:: :ocv:func:`HoughLinesP`
cuda::createHoughSegmentDetector
--------------------------------
Creates implementation for :ocv:class:`cuda::HoughSegmentDetector` .
.. ocv:function:: Ptr<HoughSegmentDetector> cuda::createHoughSegmentDetector(float rho, float theta, int minLineLength, int maxLineGap, int maxLines = 4096)
:param rho: Distance resolution of the accumulator in pixels.
:param theta: Angle resolution of the accumulator in radians.
:param minLineLength: Minimum line length. Line segments shorter than that are rejected.
:param maxLineGap: Maximum allowed gap between points on the same line to link them.
:param maxLines: Maximum number of output lines.
cuda::HoughCirclesDetector
--------------------------
.. ocv:class:: cuda::HoughCirclesDetector : public Algorithm
Base class for circles detector algorithm. ::
class CV_EXPORTS HoughCirclesDetector : public Algorithm
{
public:
virtual void detect(InputArray src, OutputArray circles) = 0;
virtual void setDp(float dp) = 0;
virtual float getDp() const = 0;
virtual void setMinDist(float minDist) = 0;
virtual float getMinDist() const = 0;
virtual void setCannyThreshold(int cannyThreshold) = 0;
virtual int getCannyThreshold() const = 0;
virtual void setVotesThreshold(int votesThreshold) = 0;
virtual int getVotesThreshold() const = 0;
virtual void setMinRadius(int minRadius) = 0;
virtual int getMinRadius() const = 0;
virtual void setMaxRadius(int maxRadius) = 0;
virtual int getMaxRadius() const = 0;
virtual void setMaxCircles(int maxCircles) = 0;
virtual int getMaxCircles() const = 0;
};
cuda::HoughCirclesDetector::detect
----------------------------------
Finds circles in a grayscale image using the Hough transform.
.. ocv:function:: void cuda::HoughCirclesDetector::detect(InputArray src, OutputArray circles)
:param src: 8-bit, single-channel grayscale input image.
:param circles: Output vector of found circles. Each vector is encoded as a 3-element floating-point vector :math:`(x, y, radius)` .
.. seealso:: :ocv:func:`HoughCircles`
cuda::createHoughCirclesDetector
--------------------------------
Creates implementation for :ocv:class:`cuda::HoughCirclesDetector` .
.. ocv:function:: Ptr<HoughCirclesDetector> cuda::createHoughCirclesDetector(float dp, float minDist, int cannyThreshold, int votesThreshold, int minRadius, int maxRadius, int maxCircles = 4096)
:param dp: Inverse ratio of the accumulator resolution to the image resolution. For example, if ``dp=1`` , the accumulator has the same resolution as the input image. If ``dp=2`` , the accumulator has half as big width and height.
:param minDist: Minimum distance between the centers of the detected circles. If the parameter is too small, multiple neighbor circles may be falsely detected in addition to a true one. If it is too large, some circles may be missed.
:param cannyThreshold: The higher threshold of the two passed to Canny edge detector (the lower one is twice smaller).
:param votesThreshold: The accumulator threshold for the circle centers at the detection stage. The smaller it is, the more false circles may be detected.
:param minRadius: Minimum circle radius.
:param maxRadius: Maximum circle radius.
:param maxCircles: Maximum number of output circles.
cuda::createGeneralizedHoughBallard
-----------------------------------
Creates implementation for generalized hough transform from [Ballard1981]_ .
.. ocv:function:: Ptr<GeneralizedHoughBallard> cuda::createGeneralizedHoughBallard()
cuda::createGeneralizedHoughGuil
--------------------------------
Creates implementation for generalized hough transform from [Guil1999]_ .
.. ocv:function:: Ptr<GeneralizedHoughGuil> cuda::createGeneralizedHoughGuil()
.. [Ballard1981] Ballard, D.H. (1981). Generalizing the Hough transform to detect arbitrary shapes. Pattern Recognition 13 (2): 111-122.
.. [Guil1999] Guil, N., González-Linares, J.M. and Zapata, E.L. (1999). Bidimensional shape detection using an invariant approach. Pattern Recognition 32 (6): 1025-1038.