OpenCV
4.0.0
Open Source Computer Vision
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Classes | |
class | cv::cuda::CornernessCriteria |
Base class for Cornerness Criteria computation. : More... | |
class | cv::cuda::CornersDetector |
Base class for Corners Detector. : More... | |
Functions | |
Ptr< CornersDetector > | cv::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) |
Creates implementation for cuda::CornersDetector . More... | |
Ptr< CornernessCriteria > | cv::cuda::createHarrisCorner (int srcType, int blockSize, int ksize, double k, int borderType=BORDER_REFLECT101) |
Creates implementation for Harris cornerness criteria. More... | |
Ptr< CornernessCriteria > | cv::cuda::createMinEigenValCorner (int srcType, int blockSize, int ksize, int borderType=BORDER_REFLECT101) |
Creates implementation for the minimum eigen value of a 2x2 derivative covariation matrix (the cornerness criteria). More... | |
Ptr<CornersDetector> cv::cuda::createGoodFeaturesToTrackDetector | ( | int | srcType, |
int | maxCorners = 1000 , |
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double | qualityLevel = 0.01 , |
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double | minDistance = 0.0 , |
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int | blockSize = 3 , |
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bool | useHarrisDetector = false , |
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double | harrisK = 0.04 |
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) |
Creates implementation for cuda::CornersDetector .
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. |
Ptr<CornernessCriteria> cv::cuda::createHarrisCorner | ( | int | srcType, |
int | blockSize, | ||
int | ksize, | ||
double | k, | ||
int | borderType = BORDER_REFLECT101 |
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Creates implementation for Harris cornerness criteria.
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. |
Ptr<CornernessCriteria> cv::cuda::createMinEigenValCorner | ( | int | srcType, |
int | blockSize, | ||
int | ksize, | ||
int | borderType = BORDER_REFLECT101 |
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) |
Creates implementation for the minimum eigen value of a 2x2 derivative covariation matrix (the cornerness criteria).
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. |