Title

基于SURF的特征点快速匹配算法

Translated Titles

Fast feature point matching algorithm based on SURF

Authors

尧思远;华北光电技术研究所;尧思远;王晓明;左帅;华北光电技术研究所,北京,100015

Key Words

SURF特征 ; 特征点匹配 ; 最近邻欧氏距离比率 ; Pearson相关系数 ; 图像与信号处理 ; SURF descriptor ; feature points matching ; Euclidean nearest neighbor distance ratio ; Pearson correlation coefficient

PublicationName

激光與紅外

Volume or Term/Year and Month of Publication

44卷3期(2014 / 05 / 06)

Page #

347 - 350

Content Language

簡體中文

Chinese Abstract

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。

English Abstract

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.

Topic Category 基礎與應用科學 > 物理
工程學 > 電機工程