Harris corner detector

dst = cv.cornerHarris(src)
dst = cv.cornerHarris(src, 'OptionName', optionValue, ...)

Input

• src Input single-channel 8-bit or floating-point image.

Output

• dst Image to store the Harris detector responses. It has the type single and the same size as src (single-channel).

Options

• BlockSize Neighborhood size (see the details on cv.cornerEigenValsAndVecs). default 5.
• KSize Aperture parameter for the cv.Sobel operator. default 3.
• K Harris detector free parameter. See the formula below. default 0.04
• BorderType Pixel extrapolation method. default 'Default'

The function runs the Harris corner detector on the image. Similarly to cv.cornerMinEigenVal and cv.cornerEigenValsAndVecs, for each pixel (x,y) it calculates a 2 x 2 gradient covariance matrix M(x,y) over a BlockSize x BlockSize neighborhood. Then, it computes the following characteristic:

 dst(x,y) = det(M(x,y)) - k * (trace(M(x,y)))^2

Corners in the image can be found as the local maxima of this response map.