Detecting the Dominant Points by the Curvature-Based Polygonal Approximation

Abstract

Detecting dominant points is an important step for object recognition. Corner detection and polygonal approximation are two major approaches for dominant point detection. In this paper, we propose the curvature-based polygonal approximation method which combines the corner detection and polygonal approximation techniques to detect the dominant points. This detection method consists of three procedures: (1) extract the break points that do not lie on a straight line, (2) detect the potential corners, and (3) perform polygonal approximation by partitioning the curves between two consecutive potential corners. Both quantitative and qualitative evaluations have been conducted. Experimental results show that the combined methods are superior to the conventional methods, and the dominant points can be properly detected by the combined methods.