Fast Polygonal Approximation Based on Genetic Algorithms

Author

Tsai, Yao-Hong

Author_Institution

Dept. of Inf. Manage., Hsuan Chuang Univ., Hsinchu

fYear

2006

fDate

10-12 July 2006

Firstpage

322

Lastpage

326

Abstract

A fast algorithm is proposed for polygonal approximation of a digitized curve based on genetic evolution. The polygon is represented by a set of dominant points. The dominant points are identified as the points on the curve with local maximum curvatures. The optimization problem for the digitized curve with the approximating polygon is employing the genetic algorithm. Thus, a chromosome is used to represent a polygon. The break point detection on the chromosome is conducted to reduce the computations for optimization. Experimental results are included to show the effectiveness of this method

Keywords

approximation theory; computational geometry; curve fitting; genetic algorithms; image processing; break point detection; digitized curve; fast polygonal approximation; genetic algorithms; genetic evolution; local maximum curvatures; optimization problem; Approximation algorithms; Biological cells; Evolutionary computation; Genetic algorithms; Image processing; Image segmentation; Information management; Pattern recognition; Shape; Smoothing methods;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer and Information Science, 2006 and 2006 1st IEEE/ACIS International Workshop on Component-Based Software Engineering, Software Architecture and Reuse. ICIS-COMSAR 2006. 5th IEEE/ACIS International Conference on

Conference_Location

Honolulu, HI

Print_ISBN

0-7695-2613-6

Type

conf

DOI

10.1109/ICIS-COMSAR.2006.39

Filename

1652011