goodfeaturestotrackcv

Syntax

R = goodfeaturestotrackcv(handle, maxCorners, quality, minDistance...)

R = goodfeaturestotrackcv(handle, maxCorners, quality, minDistance, mask, blockSize, useHDetector, freeParam)

Inputs

handle: Handle of an image.; Type: integer
maxCorners: Maximum prominent corners to detect. If value is less less than 1, all prominent corners will be detected.; Type: integer
quality: Minimal accepted quality of detected corners.; Type: scalar
minDistance: Minimum possible Euclidean distance between the detected corners.; Type: scalar
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.; Type: integer | mat
blockSize: Optional parameter specifying average block size for computation of a derivative covariation matrix in each pixel neighborhood. Defaults to 3.; Type: integer
useHDetector: Optional value set to true if Harris detector should be used. Default value is false.; Type: logical
freeParam: Optional parameter specifying the free parameter of the Harris detector. Default value is 0.04.; Type: scalar

Outputs

R: Handle of the resulting gray scale image showing prominent corners.; Type: integer

Example

Compute prominent corners in an image with default parameters:


handle = imreadcv('cv4.jpg');
maxCorners = 0;
qualityLevel = 0.01;
minDistance = 10;
R = goodfeaturestotrackcv(handle, maxCorners, qualityLevel, minDistance);