Point Pattern Matching Algorithm Based on Point Pair Topological Characteristic and Probabilistic Relaxation Labeling

被引：0

作者：

Lu Chun-yan ^{[1
]}

Zou Huan-xin ^{[1
]}

Zhao Jian ^{[1
]}

Zhou Shi-lin ^{[1
]}

机构：

[1] Natl Univ Def Technol, Sch Elect Sci & Engn, Changsha 07318457635, Hunan, Peoples R China

来源：

ELECTRONIC INFORMATION AND ELECTRICAL ENGINEERING | 2012年 / 19卷

关键词：

point pattern matching; point pair topological characteristic; probabilistic relaxation labeling; REGISTRATION;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Most of current point pattern matching algorithms perform poorly when the outliers and noises exist. To improve the accuracy and efficiency, this paper presents a novel and robust point pattern matching algorithm based on Point Pair Topological Characteristic and Probabilistic Relaxation Labeling (PPTC-PRL). A new shape descriptor, Point Pair Topological Characteristic, was first proposed. Use the newly defined point pair topological characteristic to compute a new comparability measurement as the initial association probability matrix. Then construct a robust support function based on the obtained association probability matrix. Finally, the correct matching results are achieved by using the relaxed iterations of association probability matrix. Both of the synthetic and real word data experiments showed the proposed algorithm is effective and robust.

引用

页码：98 / 102

页数：5

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