Polygonal approximation using genetic algorithms

A polygon approximation method based on genetic algorithms is proposed in this paper. In the method, a chromosome is used to represent a polygon and is represented by a binary string. Each bit, called a gene, represents a point on the object curve. The objective function is defined as the integral square error between the given curve and the approximated polygon. Three genetic operators namely selection, crossover and mutation, have been constructed for this specific problem. The proposed method when compared with three existing methods can obtain superior approximation results with less error norm with respect to the original curves. (C) 1999 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.