Polygonal approximation using genetic algorithm

Shu Chien Huang, Yung Nien Sun

研究成果: Paper同行評審

4 引文 斯高帕斯(Scopus)

摘要

Polygonal approximation is an important issue in pattern recognition and image processing. A new polygonal approximation method using genetic algorithm is proposed. Genetic algorithms are search algorithms based on the mechanisms of natural selection and natural genetics. The chromosome is used to represent an approximated polygon and is represented by a binary string. Each bit, called gene, represents a curve point. A gene with value 1 indicates that the corresponding curve point is a breakpoint of the approximated polygon. The objective function is defined as the total arc-to-chord deviation between the curve and the polygon. The proposed method is compared to two existing methods proposed by Teh-Chin [5] and Ansari-Huang [6]. Some experimental results depict the superiority of the proposed approach.

原文English
頁面469-474
頁數6
出版狀態Published - 1996
事件Proceedings of the 1996 IEEE International Conference on Evolutionary Computation, ICEC'96 - Nagoya, Jpn
持續時間: 1996 五月 201996 五月 22

Other

OtherProceedings of the 1996 IEEE International Conference on Evolutionary Computation, ICEC'96
城市Nagoya, Jpn
期間96-05-2096-05-22

All Science Journal Classification (ASJC) codes

  • 工程 (全部)

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