DocumentCode :
2875202
Title :
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
Link To Document :
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