Class implementing edge detection algorithm from [51] :
More...
#include <opencv2/ximgproc/structured_edge_detection.hpp>
|
virtual void | computeOrientation (cv::InputArray _src, cv::OutputArray _dst) const =0 |
| The function computes orientation from edge image. More...
|
|
virtual void | detectEdges (cv::InputArray _src, cv::OutputArray _dst) const =0 |
| The function detects edges in src and draw them to dst. More...
|
|
virtual void | edgesNms (cv::InputArray edge_image, cv::InputArray orientation_image, cv::OutputArray _dst, int r=2, int s=0, float m=1, bool isParallel=true) const =0 |
| The function edgenms in edge image and suppress edges where edge is stronger in orthogonal direction. More...
|
|
| Algorithm () |
|
virtual | ~Algorithm () |
|
virtual void | clear () |
| Clears the algorithm state. More...
|
|
virtual bool | empty () const |
| Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read. More...
|
|
virtual String | getDefaultName () const |
|
virtual void | read (const FileNode &fn) |
| Reads algorithm parameters from a file storage. More...
|
|
virtual void | save (const String &filename) const |
|
virtual void | write (FileStorage &fs) const |
| Stores algorithm parameters in a file storage. More...
|
|
void | write (const Ptr< FileStorage > &fs, const String &name=String()) const |
| simplified API for language bindings This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts. More...
|
|
Class implementing edge detection algorithm from [51] :
◆ computeOrientation()
Python: |
---|
| _dst | = | cv.ximgproc_StructuredEdgeDetection.computeOrientation( | _src[, _dst] | ) |
The function computes orientation from edge image.
- Parameters
-
_src | edge image. |
_dst | orientation image. |
◆ detectEdges()
Python: |
---|
| _dst | = | cv.ximgproc_StructuredEdgeDetection.detectEdges( | _src[, _dst] | ) |
The function detects edges in src and draw them to dst.
The algorithm underlies this function is much more robust to texture presence, than common approaches, e.g. Sobel
- Parameters
-
_src | source image (RGB, float, in [0;1]) to detect edges |
_dst | destination image (grayscale, float, in [0;1]) where edges are drawn |
- See also
- Sobel, Canny
◆ edgesNms()
Python: |
---|
| _dst | = | cv.ximgproc_StructuredEdgeDetection.edgesNms( | edge_image, orientation_image[, _dst[, r[, s[, m[, isParallel]]]]] | ) |
The function edgenms in edge image and suppress edges where edge is stronger in orthogonal direction.
- Parameters
-
edge_image | edge image from detectEdges function. |
orientation_image | orientation image from computeOrientation function. |
_dst | suppressed image (grayscale, float, in [0;1]) |
r | radius for NMS suppression. |
s | radius for boundary suppression. |
m | multiplier for conservative suppression. |
isParallel | enables/disables parallel computing. |
The documentation for this class was generated from the following file: