Calculates the minimal eigenvalue of gradient matrices for corner detection

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

Input

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

Output

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

Options

• BlockSize Neighborhood size (see the details on cv.cornerEigenValsAndVecs). default 5.
• KSize Aperture parameter for the cv.Sobel operator. default 3.
• BorderType Pixel extrapolation method. See cv.copyMakeBorder. default 'Default'

The function is similar to cv.cornerEigenValsAndVecs but it calculates and stores only the minimal eigenvalue of the covariance matrix of derivatives, that is, min(lambda_1,lambda_2) in terms of the formulae in the cv.cornerEigenValsAndVecs description.