A nonlinear algorithm for critical point detection

Abstract

The authors present a nonlinear algorithm for critical point detection (CPD). The algorithm eliminates the problems arising from curvature approximation and Gaussian filtering in the existing algorithms. By defining a "critical level" as the modified area confined by three consecutive "pseudo-critical points", a simple but very effective algorithm is developed. The comparison of the experimental results with those of many other CPD algorithms shows that the proposed algorithm is superior in all tested contours.<>