A Fast Matching Algorithm Based on Local Binary Patterns and Graph Transformation

被引：0
作者：
Zhao X.-Q. [1 ]
Yue Z.-D. [1 ]
机构：
[1] College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou, 730050, Gansu
来源：
Tien Tzu Hsueh Pao/Acta Electronica Sinica | 2017年 / 45卷 / 09期
关键词：
Graph transformation matching; Image matching; Local binary patterns; Scale invariant feature transform;
D O I：
10.3969/j.issn.0372-2112.2017.09.015
中图分类号：
学科分类号：
摘要：
Aiming at problems of large computation and poor real-time of scale invariant feature transform (SIFT) algorithm for image matching application in image matching, object recognition and other fields, a matching algorithm based on local binary patterns (LBP) and graph transformation matching (GTM) is proposed. Firstly, SIFT is used to extract initial feature points. 13×13 pixel blocks around the feature points are used as the feature regions. Secondly, in order to reduce complexity of descriptors, the local rotation invariant binary patterns (LRIBP) descriptor is used to produce feature vectors of 29 dimensions for a feature region. Euclidean distance is adopted as measure criterion of the descriptors to fulfil initial match. Finally, GTM is adopted to eliminate mismatching points. Simulation results show that the proposed algorithm not only improves accuracy and robustness and real-time, but also reduces the amount of calculation. © 2017, Chinese Institute of Electronics. All right reserved.
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页码：2156 / 2161
页数：5
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