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. 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.