Applies Ridge Detection Filter to an input image. Implements Ridge detection similar to the one in Mathematica using the eigen values from the Hessian Matrix of the input image using Sobel Derivatives. Additional refinement can be done using Skeletonization and Binarization. Adapted from [61] and [160].
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#include <opencv2/ximgproc/ridgefilter.hpp>
Applies Ridge Detection Filter to an input image. Implements Ridge detection similar to the one in Mathematica using the eigen values from the Hessian Matrix of the input image using Sobel Derivatives. Additional refinement can be done using Skeletonization and Binarization. Adapted from [61] and [160].
◆ create()
Python: |
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| retval | = | cv.ximgproc.RidgeDetectionFilter_create( | [, ddepth[, dx[, dy[, ksize[, out_dtype[, scale[, delta[, borderType]]]]]]]] | ) |
Create pointer to the Ridge detection filter.
- Parameters
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ddepth | Specifies output image depth. Defualt is CV_32FC1 |
dx | Order of derivative x, default is 1 |
dy | Order of derivative y, default is 1 |
ksize | Sobel kernel size , default is 3 |
out_dtype | Converted format for output, default is CV_8UC1 |
scale | Optional scale value for derivative values, default is 1 |
delta | Optional bias added to output, default is 0 |
borderType | Pixel extrapolation method, default is BORDER_DEFAULT |
- See also
- Sobel, threshold, getStructuringElement, morphologyEx.( for additional refinement)
◆ getRidgeFilteredImage()
virtual void cv::ximgproc::RidgeDetectionFilter::getRidgeFilteredImage |
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InputArray |
_img, |
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OutputArray |
out |
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pure virtual |
Python: |
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| out | = | cv.ximgproc_RidgeDetectionFilter.getRidgeFilteredImage( | _img[, out] | ) |
Apply Ridge detection filter on input image.
- Parameters
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_img | InputArray as supported by Sobel. img can be 1-Channel or 3-Channels. |
out | OutputAray of structure as RidgeDetectionFilter::ddepth. Output image with ridges. |
The documentation for this class was generated from the following file: