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Open Source Computer Vision Library
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122 lines
4.8 KiB
122 lines
4.8 KiB
Feature Detection |
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================= |
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.. highlight:: cpp |
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cuda::CornernessCriteria |
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.. ocv:class:: cuda::CornernessCriteria : public Algorithm |
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Base class for Cornerness Criteria computation. :: |
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class CV_EXPORTS CornernessCriteria : public Algorithm |
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{ |
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public: |
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virtual void compute(InputArray src, OutputArray dst, Stream& stream = Stream::Null()) = 0; |
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}; |
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cuda::CornernessCriteria::compute |
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--------------------------------- |
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Computes the cornerness criteria at each image pixel. |
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.. ocv:function:: void cuda::CornernessCriteria::compute(InputArray src, OutputArray dst, Stream& stream = Stream::Null()) |
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:param src: Source image. |
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:param dst: Destination image containing cornerness values. It will have the same size as ``src`` and ``CV_32FC1`` type. |
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:param stream: Stream for the asynchronous version. |
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cuda::createHarrisCorner |
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------------------------ |
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Creates implementation for Harris cornerness criteria. |
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.. ocv:function:: Ptr<CornernessCriteria> cuda::createHarrisCorner(int srcType, int blockSize, int ksize, double k, int borderType = BORDER_REFLECT101) |
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:param srcType: Input source type. Only ``CV_8UC1`` and ``CV_32FC1`` are supported for now. |
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:param blockSize: Neighborhood size. |
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:param ksize: Aperture parameter for the Sobel operator. |
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:param k: Harris detector free parameter. |
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:param borderType: Pixel extrapolation method. Only ``BORDER_REFLECT101`` and ``BORDER_REPLICATE`` are supported for now. |
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.. seealso:: :ocv:func:`cornerHarris` |
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cuda::createMinEigenValCorner |
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Creates implementation for the minimum eigen value of a 2x2 derivative covariation matrix (the cornerness criteria). |
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.. ocv:function:: Ptr<CornernessCriteria> cuda::createMinEigenValCorner(int srcType, int blockSize, int ksize, int borderType = BORDER_REFLECT101) |
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:param srcType: Input source type. Only ``CV_8UC1`` and ``CV_32FC1`` are supported for now. |
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:param blockSize: Neighborhood size. |
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:param ksize: Aperture parameter for the Sobel operator. |
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:param borderType: Pixel extrapolation method. Only ``BORDER_REFLECT101`` and ``BORDER_REPLICATE`` are supported for now. |
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.. seealso:: :ocv:func:`cornerMinEigenVal` |
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cuda::CornersDetector |
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--------------------- |
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.. ocv:class:: cuda::CornersDetector : public Algorithm |
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Base class for Corners Detector. :: |
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class CV_EXPORTS CornersDetector : public Algorithm |
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{ |
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public: |
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virtual void detect(InputArray image, OutputArray corners, InputArray mask = noArray()) = 0; |
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}; |
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cuda::CornersDetector::detect |
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Determines strong corners on an image. |
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.. ocv:function:: void cuda::CornersDetector::detect(InputArray image, OutputArray corners, InputArray mask = noArray()) |
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:param image: Input 8-bit or floating-point 32-bit, single-channel image. |
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:param corners: Output vector of detected corners (1-row matrix with CV_32FC2 type with corners positions). |
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:param 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. |
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cuda::createGoodFeaturesToTrackDetector |
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--------------------------------------- |
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Creates implementation for :ocv:class:`cuda::CornersDetector` . |
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.. ocv:function:: 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) |
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:param srcType: Input source type. Only ``CV_8UC1`` and ``CV_32FC1`` are supported for now. |
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:param maxCorners: Maximum number of corners to return. If there are more corners than are found, the strongest of them is returned. |
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:param 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 :ocv:func:`cornerMinEigenVal` ) or the Harris function response (see :ocv:func:`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. |
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:param minDistance: Minimum possible Euclidean distance between the returned corners. |
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:param blockSize: Size of an average block for computing a derivative covariation matrix over each pixel neighborhood. See :ocv:func:`cornerEigenValsAndVecs` . |
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:param useHarrisDetector: Parameter indicating whether to use a Harris detector (see :ocv:func:`cornerHarris`) or :ocv:func:`cornerMinEigenVal`. |
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:param harrisK: Free parameter of the Harris detector. |
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.. seealso:: :ocv:func:`goodFeaturesToTrack`
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