goodfeaturestotrackcv
Finds prominent corners in an image.
Syntax
R = goodfeaturestotrackcv(handle, maxCorners, quality, minDistance...)
R = goodfeaturestotrackcv(handle, maxCorners, quality, minDistance, mask, blockSize, useHDetector, freeParam)
Inputs
- handle
- Handle of an image.
- maxCorners
- Maximum prominent corners to detect. If value is less less than 1, all prominent corners will be detected.
- quality
- Minimal accepted quality of detected corners.
- minDistance
- Minimum possible Euclidean distance between the detected corners.
- mask
- Optional handle of an 8-bit single channel image or a 2D matrix of natural numbers representing the region of interest where prominent corners are detected in R. If specified it must have the same dimensions as handle.
- blockSize
- Optional parameter specifying average block size for computation of a derivative covariation matrix in each pixel neighborhood. Defaults to 3.
- useHDetector
- Optional value set to true if Harris detector should be used. Default value is false.
- freeParam
- Optional parameter specifying the free parameter of the Harris detector. Default value is 0.04.
Outputs
- R
- Handle of the resulting gray scale image showing prominent corners.
Example
handle = imreadcv('cv4.jpg');
maxCorners = 0;
qualityLevel = 0.01;
minDistance = 10;
R = goodfeaturestotrackcv(handle, maxCorners, qualityLevel, minDistance);