云南师范大学学报（自然科学版）2018，Vol.38Issue(2)：56-59,4.DOI:10.7699/j.ynnu.ns-2018-024
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
摘要
Abstract
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Key words
Image matching/Scale invariant feature transform(SIFT)/Kernel projection/Particle swarm optimization分类
数理科学引用本文复制引用
陈文华,岳雅,余本国..一种粒子群优化的改进SIFT特征点的图像匹配[J].云南师范大学学报（自然科学版）,2018,38(2):56-59,4.基金项目
山西省教育厅教改计划资助项目(127/11011904). （127/11011904）
