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Improved image matching method based on cursory search and detail-oriented correction with extension window

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Abstract

In order to achieve the fast and accurate image matching, gray matching algorithm and SIFT feature matching algorithm are combined, and an approach to the cursory search and detail-oriented correction with extension window is proposed. The cursory search is achieved by using new adaptive optimal guidance artificial bee colony algorithm (AOGABC) instead of ergodicity of the traditional gray matching algorithm. The gray correlation degree with statistical properties serves as the fitness function of the artificial colony algorithm (ABC). The extensional image window has built after cutting image according to the extension rules in extension window, detail-oriented correction accurately matches image by using the SIFT algorithm. The experiments verify that the matching method not only realizes rapidity because of performance of artificial bee colony algorithm and gray relational grade in the cursory search, but also achieves matching accuracy resulted from the combination of SIFT algorithm and extension window in this paper. By comparing the effects of different algorithms in the typical image, the results show that the purpose of the exact match is achieved.

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Acknowledgements

This work was supported in part by the National Natural Science Foundation of China under Grants 61374127 and 51404073, the Outstanding Youth Science Foundation of National Natural Science Foundation of China under Grant 61422301, the Chinese Postdoctoral Science Foundation under Grant 2014 M550180, the Scientific Research Fund of Heilongjiang Provincial Department of Education under Grant 12541090, and the Excellent Youth Foundation of Heilongjiang Scientific Committee JC2015016.

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Authors and Affiliations

  1. School of Electrical Information Engineering, Northeast Petroleum University, Daqing, 163318, China

    Fengcai Huo, Di Wang & Weijian Ren

  2. China Power Puhua Information Technology Company Limited, Beijing, 100085, China

    Ying Du

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  1. Fengcai Huo
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  2. Di Wang
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  3. Weijian Ren
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Correspondence to Di Wang.

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Huo, F., Wang, D., Ren, W. et al. Improved image matching method based on cursory search and detail-oriented correction with extension window. Multimed Tools Appl 77, 28885–28904 (2018). https://doi.org/10.1007/s11042-018-6070-x

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  • DOI: https://doi.org/10.1007/s11042-018-6070-x

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