文章基本信息

标题：A Method of Image Registration Based On Best Similarity of Local Geometric Figure
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作者：Jiang, Zetao ; Zhou, Le ; Zhang, Liwen 等
期刊名称：Journal of Software
印刷版ISSN：1796-217X
出版年度：2014
卷号：9
期号：4
页码：964-969
DOI：10.4304/jsw.9.4.964-969
语种：English
出版社：Academy Publisher
摘要：Image Registration is an important part of computer vision. We propose a method of image registration by obtaining best similarity of local geometric figure that utilizes opposite core difference (OCD) of corresponding local figure. This method gets initial matching after describing precisely SIFT points by constructing feature subspaces based on the detection of SIFT feature points. Then we describe the corresponding similarity by OCD of local figure constructed by SIFT points and choose the feature points that possess highest similarity measure as point set to compute projective transformation matrix . Experiments have proved that the precision of the matrix and the Image matching is at a high level.
关键词：SIFT feature subspace;local geometric similarity;projective;OCD