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An improved cultural algorithm and its application in image matching

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Abstract

Cultural Algorithm (CA) are a class of computational models derived from observing the cultural evolution process in nature and is used to solve complex calculations of the new global optimization search algorithms. Aiming at the traditional cultural algorithm has poor precision and trap into local optimum of global optimization. In this paper, introduce the isolation niche technology into the traditional cultural algorithm. With improvements, the algorithm is less likely to trap in local optimum. According to the test of one set of benchmark function, the proposed algorithm has greater improvements than ordinal cultural algorithm in the aspects of convergence precision and stability. In this paper, introduce the proposed algorithm into the image matching problem, and the simulation test shows that the algorithm for image matching problem has made great effects in stability and convergence precision.

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Acknowledgements

This paper is supported by National Natural Science Foundation of China (No. 41404076, 61402425, 61501412, 61673354, 61672474).

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Authors and Affiliations

  1. School of Computer Science, China University of Geosciences, Wuhan, Hubei, 430074, China

    Xuesong Yan

  2. Center of Network and Educational Technology, Chin University of Geosciences, Wuhan, Hubei, 430074, China

    Tao Song

  3. Faculty of Computer Science and Engineering, WuHan Institute of Technology, Wuhan, Hubei, 430074, China

    Qinghua Wu

Authors
  1. Xuesong Yan
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  2. Tao Song
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  3. Qinghua Wu
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Corresponding author

Correspondence to Qinghua Wu.

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Yan, X., Song, T. & Wu, Q. An improved cultural algorithm and its application in image matching. Multimed Tools Appl 76, 14951–14968 (2017). https://doi.org/10.1007/s11042-016-4313-2

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  • DOI: https://doi.org/10.1007/s11042-016-4313-2

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