A new point matching method based on position similarity

Jun Jun Pan, Yan Ning Zhang

科研成果: 书/报告/会议事项章节会议稿件同行评审

2 引用 (Scopus)

摘要

A new corresponding point matching method is presented when studying the feature points matching from X-ray images, which is called "the regulation of the minimum summation of Euclid distance". This method is different from the conventional matching approaches based on gray level or based on region geometric feature. It is based on the position similarity of corresponding points. This method derives from the model of sequence matching algorithm. According to the condition that the relative position of any two points in adjacent area from two correlative images are almost constant, this method minimizes the summation of corresponding points distance by adjusting the sequence of points through evolutionary programming searching. The experimental result shows that this method can match the most feature points correctly in low time-consuming, just based on the position similarity of points.

源语言英语
主期刊名2005 International Conference on Machine Learning and Cybernetics, ICMLC 2005
5154-5158
页数5
出版状态已出版 - 2005
活动International Conference on Machine Learning and Cybernetics, ICMLC 2005 - Guangzhou, 中国
期限: 18 8月 200521 8月 2005

出版系列

姓名2005 International Conference on Machine Learning and Cybernetics, ICMLC 2005

会议

会议International Conference on Machine Learning and Cybernetics, ICMLC 2005
国家/地区中国
Guangzhou
时期18/08/0521/08/05

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