Improved image matching algorithm based on LK optical flow and grid motion statistics Online publication date: Mon, 06-Jun-2022
by Qunpo Liu; Xiulei Xi; Weicun Zhang; Lingxiao Yang; Naohiko Hanajima
International Journal of Computer Applications in Technology (IJCAT), Vol. 68, No. 1, 2022
Abstract: In order to solve the problems of low accuracy and long time-consuming of AKAZE algorithm in the image matching of glass encapsulated electrical connectors, an improved image matching algorithm based on LK optical flow and grid motion statistics is proposed. Matching points are obtained by calculating the matching area which are made up of the feature points for conditional constraints. In the local feature matching algorithm, large amount of calculation is an urgent problem as a result of sparse neighbourhood consistency feature cannot define adjacent areas well. The false matching points are removed by improved grid motion statistics algorithm based on integrates FLANN algorithm, and then match computation time is reduced. The performance is verified by experiments based on the Mikolajczyk and actual scene data. Experiment results show that the proposed algorithm can handle the actual scene data, the CMR reaches over 93%, and the time is within 0.4s.
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