Determination of optimal polygonal approximation using genetic algorithms

Author

Huang, Shu-chien ; Sun, Yung-Nien

Author_Institution

Dept. of Comput. Sci. & Inf. Eng., Nat. Cheng Kung Univ., Tainan, Taiwan

fYear

1998

fDate

4-9 May 1998

Firstpage

124

Lastpage

129

Abstract

A new polygonal approximation algorithm is presented which gives the minimum number of sides for the approximated polygon under a uniform error norm. In the proposed 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 given curve. The convergence of the method is guaranteed and optimal or near-optimal solutions can be obtained. Some experimental results depict the feasibility of the proposed approach

Keywords

approximation theory; computational geometry; convergence of numerical methods; error analysis; genetic algorithms; pattern recognition; binary string; chromosome; convergence; genes; genetic algorithms; minimum side number; near-optimal solutions; optimal polygonal approximation; uniform error norm; Approximation algorithms; Biological cells; Clocks; Computer errors; Computer science; Genetic algorithms; Iterative algorithms; Pattern recognition; Piecewise linear approximation; Sun;

fLanguage

English

Publisher

ieee

Conference_Titel

Evolutionary Computation Proceedings, 1998. IEEE World Congress on Computational Intelligence., The 1998 IEEE International Conference on

Conference_Location

Anchorage, AK

Print_ISBN

0-7803-4869-9

Type

conf

DOI

10.1109/ICEC.1998.699392

Filename

699392