A gray-level corner detector using fuzzy logic

A real-time gray-level corner detector is developed. The gray-level corner detection problem is formulated as a pattern classification problem to determine whether a pixel belongs to the class of corners or not. The developed pattern classifier is based on the Bayesian classifier, and the probability density function is estimated by means of fuzzy logic. For the purpose of localizing gray-level corners, a one-pass local maximum point detector is developed. Also, hardware implementation of the developed algorithm is studied to detect the corners in real time.