CAJ | 학술논문

为了解决光电图像匹配过程中特征点错配率较高的问题，本文提出了一种基于SURF特征点的匹配方法。该算法首先利用最近邻欧氏距离比率法对提取的SURF特征做粗匹配，然后获取特征点对应尺度的邻域灰度统计信息，进而利用Pearson相关系数比得到鲁棒性较强的匹配对。实验表明该方法能够有效提高匹配的准确率，且满足实时性要求。
위료해결광전도상필배과정중특정점착배솔교고적문제，본문제출료일충기우SURF특정점적필배방법。해산법수선이용최근린구씨거리비솔법대제취적SURF특정주조필배，연후획취특정점대응척도적린역회도통계신식，진이이용Pearson상관계수비득도로봉성교강적필배대。실험표명해방법능구유효제고필배적준학솔，차만족실시성요구。
In order to solve the problem of the high mismatching rate of feature points in course of image matching,a novel matching strategy based on SURF feature points is propose.Euclidean nearest neighbor distance ratio method is used to match the extracted SURF features roughly,and then statistical information of the corresponding gray neigh-borhood of each feature point is obtained.Then,more robustness matching pairs can be gotten with Pearson correla-tion coefficient.Experimental results show that this method can effectively improve the matching accuracy and meet real-time requirements.