一种粒子群优化的改进SIFT特征点的图像匹配  

An Image Matching Method of Improved SIFT Algorithm Based on Particle Swarm Optimization Algorithm

作　　者：陈文华 岳雅[2] 余本国[1] CHEN Wen-hua;YUE Ya;YU Ben-guo(School of Science, North University of China, Taiyuan 030051, China;Aerospace Power Test Technology Institute of Xi＇an,Xi＇an 710100,China)

机构地区：[1]中北大学理学院,山西太原030051 [2]西安航天动力试验技术研究所,陕西西安710100

出　　处：《云南师范大学学报（自然科学版）》2018年第2期56-59,共4页Journal of Yunnan Normal University:Natural Sciences Edition

基　　金：山西省教育厅教改计划资助项目(127/11011904)

摘　　要：首先采用内核投影算法Walsh-Hadamard降低了生成的SIFT特征描述子的特征维度;然后在基于距离相似度度量基础上加入方向约束,减少误配率;最后使用粒子群算法对搜索策略进行优化,减少算法耗时.实验结果表明,该改进算法有效提高了图像匹配准确率.Firstly,the kernel projection algorithm Walsh-Hadamard is used to reduce the SIFT feature descriptor.Then based on the measure of distance similarity,the direction constraint is added to reduce the mismatch rate.Finally the PSO algorithm is used to optimize the search strategy to reduce the time-consuming of the algorithm.Experimental results show that the improved algorithm can effectively improve the accuracy of image matching.

关 键 词：图像匹配 SIFT 内核投影 粒子群 

分 类 号：O29[理学—应用数学]