Optimal polygonal approximation of digital planar curves using meta heuristics

被引：14
|
作者：
Zhang, HB [1 ]
Guo, JJ [1 ]
机构：
[1] Beijing Polytech Univ, Comp Inst, Beijing 100044, Peoples R China
来源：
PATTERN RECOGNITION | 2001年 / 34卷 / 07期
基金：
中国国家自然科学基金;
关键词：
digital planar curves; polygonal approximation; genetic algorithm; pareto optimal solution; tabu search;
D O I：
10.1016/S0031-3203(00)00097-2
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper presents three heuristic algorithms For optimal polygonal approximation of digital planar curves. We use genetic algorithm (GR), improved genetic algorithm based on Pareto optimal solution (GAP) and tabu search (TS) to obtain a near optimal polygonal approximation. Compared to the famous Teh-Chin algorithm, our algorithms have obtained the approximated polygons with less number of vertices and less approximation error. Compared to the dynamic programming algorithm, the processing time of our algorithms are much less. (C) 2001 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.
引用
收藏
页码：1429 / 1436
页数：8
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