Feature Detection

cuda::CornernessCriteria

class cuda::CornernessCriteria : public Algorithm

Base class for Cornerness Criteria computation.

class CV_EXPORTS CornernessCriteria : public Algorithm
{
public:
    virtual void compute(InputArray src, OutputArray dst, Stream& stream = Stream::Null()) = 0;
};

cuda::CornernessCriteria::compute

Computes the cornerness criteria at each image pixel.

C++: void cuda::CornernessCriteria::compute(InputArray src, OutputArray dst, Stream& stream=Stream::Null())

Parameters:

• src – Source image.
• dst – Destination image containing cornerness values. It will have the same size as src and CV_32FC1 type.
• stream – Stream for the asynchronous version.

cuda::createHarrisCorner

Creates implementation for Harris cornerness criteria.

C++: Ptr<CornernessCriteria> cuda::createHarrisCorner(int srcType, int blockSize, int ksize, double k, int borderType=BORDER_REFLECT101)

Parameters:

• srcType – Input source type. Only CV_8UC1 and CV_32FC1 are supported for now.
• blockSize – Neighborhood size.
• ksize – Aperture parameter for the Sobel operator.
• k – Harris detector free parameter.
• borderType – Pixel extrapolation method. Only BORDER_REFLECT101 and BORDER_REPLICATE are supported for now.

See also

cornerHarris()

cuda::createMinEigenValCorner

Creates implementation for the minimum eigen value of a 2x2 derivative covariation matrix (the cornerness criteria).

C++: Ptr<CornernessCriteria> cuda::createMinEigenValCorner(int srcType, int blockSize, int ksize, int borderType=BORDER_REFLECT101)

Parameters:

• srcType – Input source type. Only CV_8UC1 and CV_32FC1 are supported for now.
• blockSize – Neighborhood size.
• ksize – Aperture parameter for the Sobel operator.
• borderType – Pixel extrapolation method. Only BORDER_REFLECT101 and BORDER_REPLICATE are supported for now.

See also

cornerMinEigenVal()

cuda::CornersDetector

class cuda::CornersDetector : public Algorithm

Base class for Corners Detector.

class CV_EXPORTS CornersDetector : public Algorithm
{
public:
    virtual void detect(InputArray image, OutputArray corners, InputArray mask = noArray()) = 0;
};

cuda::CornersDetector::detect

Determines strong corners on an image.

C++: void cuda::CornersDetector::detect(InputArray image, OutputArray corners, InputArray mask=noArray())

Parameters:

• image – Input 8-bit or floating-point 32-bit, single-channel image.
• corners – Output vector of detected corners (1-row matrix with CV_32FC2 type with corners positions).
• mask – Optional region of interest. If the image is not empty (it needs to have the type CV_8UC1 and the same size as image ), it specifies the region in which the corners are detected.

cuda::createGoodFeaturesToTrackDetector

Creates implementation for cuda::CornersDetector .

C++: Ptr<CornersDetector> cuda::createGoodFeaturesToTrackDetector(int srcType, int maxCorners=1000, double qualityLevel=0.01, double minDistance=0.0, int blockSize=3, bool useHarrisDetector=false, double harrisK=0.04)

Parameters:

• srcType – Input source type. Only CV_8UC1 and CV_32FC1 are supported for now.
• maxCorners – Maximum number of corners to return. If there are more corners than are found, the strongest of them is returned.
• qualityLevel – Parameter characterizing the minimal accepted quality of image corners. The parameter value is multiplied by the best corner quality measure, which is the minimal eigenvalue (see cornerMinEigenVal() ) or the Harris function response (see cornerHarris() ). The corners with the quality measure less than the product are rejected. For example, if the best corner has the quality measure = 1500, and the qualityLevel=0.01 , then all the corners with the quality measure less than 15 are rejected.
• minDistance – Minimum possible Euclidean distance between the returned corners.
• blockSize – Size of an average block for computing a derivative covariation matrix over each pixel neighborhood. See cornerEigenValsAndVecs() .
• useHarrisDetector – Parameter indicating whether to use a Harris detector (see cornerHarris()) or cornerMinEigenVal().
• harrisK – Free parameter of the Harris detector.

See also

goodFeaturesToTrack()