Research on Image Registration and Mosaic Based on Vector Similarity Matching Principle

摘要：

Scale invariant feature transform (SIFT) is a better corner extraction algorithm, but there are still mismatching problems in the feature matching step. A new matching principle based on vector similarity is proposed and then it is compared with traditional matching principle. Firstly, the matching feature points are detected by the new principle. Mismatching points are further removed by using the mutual mapping theory. Secondly, transformation matrix is calculated by random sample consensus (RANSAC). Furthermore, the matrix is optimized by LevenbergMarquardt algorithm (L-M). Lastly, image mosaic is realized by image fusion. Experimental results indicate that compared with traditional matching principle, new matching principle has improved matching accuracy. It is able to apply new principle to image registration and image mosaic.

关键词： image mosaic SIFT algorithm feature matching vector similarity mutual mapping

作者: Jia Qin Jianfeng Yang Bin Xue Fan Bu

作者单位: Key Laboratory of Spectrum Imaging Technology, Xian Institute of Optics and Precision Mechanics, CA Key Laboratory of Spectrum Imaging Technology, Xian Institute of Optics and Precision Mechanics, CA

会议类型: 国际会议

会议名称: 2012 Fifth International Symposium on Computational Intelligence and Design 第五届计算智能与设计国际会议 ISCID 2012

会议地点: 杭州

会议语种:英文

页码: 901-904

在线出版日期: 2012-10-28（万方平台首次上网日期，不代表论文的发表时间）