多视角图像的图变换匹配算法

摘要

To improve the matching accuracy of different view images,a graph transformation matching algorithm for multi-view images was proposed.Initial feature point matching was got using the traditional image matching.The Euclidean distance be-tween feature points was calculated.Nearest neighbor graphs were built to determine whether the initial match was correct.The feature points matching errors were eliminated,so as to improve the matching accuracy of the multi-view images.The algorithm was compared with the random sample consensus algorithm,graph transformation matching algorithm and the iterative graph transformation matching algorithm (RANSAC)through multi group experiments.The results show that the proposed algorithm can improve precision ratio of the correct matching points and the recall ratio of wrong matching points,which verifies the effec-tiveness of the algorithm in multi-view images matching.%为提高不同视角图像的匹配精度,提出一种多视角图像的图变换匹配算法.利用传统图像匹配算法获取多视角图像特征点的初始匹配关系;计算特征点之间的欧氏距离,建立近邻图判断初始匹配的正确性;对错误的特征匹配关系进行剔除,提高图像的匹配精度.多组不同场景的多视角图像实验结果表明,与随机采样一致性算法(random sample consen-sus,RANSAC)、图变换匹配算法以及迭代的图变换匹配算法进行对比,该算法在正确匹配点对的查准率及错误匹配点对的查全率上均取得较好结果,验证了其在多视角图像匹配上的有效性.