ON CURVE MATCHING

被引:131
作者
WOLFSON, HJ [1 ]
机构
[1] TEL AVIV UNIV, SACKLER SCH MED, DEPT COMP SCI, TEL AVIV, ISRAEL
基金
美国国家科学基金会;
关键词
Computer vision; curvature; curve matching; machine intelligence; object recognition; part assembly; pattern recognition; string matching;
D O I
10.1109/34.55108
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Two algorithms to find the longest common subcurve of two 2-D curves are presented. These algorithms are based on conversion of the curves into shape signature strings and application of string matching techniques to find long matching substrings. Then direct curve matching is applied to the corresponding ‘candidate’ subcurves to find the longest matching subcurve. The first algorithm is of complexity O(n), where n is the number of sample points on the curves. The second one, while being theoretically somewhat less efficient, proved to be robust and efficient in practical applications. Both algorithms solve the problem for general curves without being dependent on some set of special points on the curves. The algorithms have industrial applications to problems of object assembly and object recognition. Experimental results are included. The algorithms can be easily extended to the 3-D case. © 1990 IEEE
引用
收藏
页码:483 / 489
页数:7
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