文章基本信息

标题：An Improved Harris-SIFT Algorithm Based on Rotation-invariant LBP Operator
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作者：Lei Yang ; Yanyun Ren ; Jiyuan Cai 等
期刊名称：International Journal of Signal Processing, Image Processing and Pattern Recognition
印刷版ISSN：2005-4254
出版年度：2016
卷号：9
期号：6
页码：159-170
DOI：10.14257/ijsip.2016.9.6.14
出版社：SERSC
摘要：Feature-points matching is an important concept in binocular stereo vision. The procession of multi-scale feature-points matching in classical Harris-SIFT algorithm is time-consuming and has high complexity when describing the feature-points. This paper proposed a new improved Harris-SIFT algorithm based on rotation-invariant LBP (Local binary patterns) operator. Firstly, the Harris operator is used to extract feature points from DOG (Difference of Gaussian) scale space. Then, the dominant direction of feature point is calculated and 81-dimensional rotation-invariant LBP descriptors are extracted when the rotation matching window is coordinated to this direction. At last, Best-Bin-First (BBF) algorithm is used to search the matching points between the two sets of feature points. Experimental results show that the proposed algorithm is lower time-consuming than classical Harris-SIFT algorithm and remains the similar matching correct rate.
关键词：Harris-SIFT; DOG (Difference of Gaussian) scale space; ; rotation-invariant LBP operator; Best-Bin-First (BBF) algorithm