Partial shape matching using genetic algorithms

被引：34
|
作者：
Ozcan, E [1 ]
Mohan, CK [1 ]
机构：
[1] Syracuse Univ, Dept Elect Engn & Comp Sci, Ctr Sci & Technol 2 120, Syracuse, NY 13244 USA
来源：
PATTERN RECOGNITION LETTERS | 1997年 / 18卷 / 10期
关键词：
partial shape matching; genetic algorithms; attributed strings; pattern recognition;
D O I：
10.1016/S0167-8655(97)00123-2
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Shape recognition is a challenging task when images contain overlapping, noisy, occluded, partial shapes. This paper addresses the task of matching input shapes with model shapes described in terms of features such as line segments and angles. The quality of matching is gauged using a measure derived from attributed shape grammars. We apply genetic algorithms to the partial shape-matching task. Preliminary results, using model shapes with 6 to 70 features each, are extremely encouraging. (C) 1997 Elsevier Science B.V.
引用
收藏
页码：987 / 992
页数：6
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