Anisotropic diffusion for effective shape corner point detection

This work presents a new method for detecting shape corner points. These points are characterized as having high curvature value and their detection is an important task in several applications, including motion tracking and object recognition. As noisy points also have high curvature value we propose a framework that includes smoothing and corner point localization. First, we defined a function that associates each shape contour point with its curvature value, then the proposed method automatically smooths this function via an anisotropic filter based on an evolutionary equation, simultaneously localizing the corner points. The results obtained show that the proposed model has good performance when compared with three other techniques.