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Multilevel thresholding using an improved cuckoo search algorithm for image segmentation

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Abstract

Multilevel thresholding image segmentation is an important technique, which has attracted much attention in recent years. The conventional exhaustive search method for image segmentation is efficient for bilevel thresholding. However, they are time expensive when dealing with multilevel thresholding image segmentation. To better tackle this problem, an improved cuckoo search algorithm (ICS) is proposed to search for the optimal multilevel thresholding in this paper, and Otsu is considered as its objective function. In the ICS, two modifications are used to improve the standard cuckoo search algorithm. First, a parameter adaptation strategy is utilized to improve exploration performance. Second, a dynamic weighted random-walk method is adopted to enhance the local search efficiency. A total of six benchmark test images are used to perform the experiments, and seven state-of-the-art metaheuristic algorithms are introduced to compare with the ICS. A series of measure indexes such as objective function value and standard deviation, PSNR, FSIM, and SSIM as well as the Wilcoxon rank sum and convergence performance are performed in the experiments; the experimental results show that the proposed algorithm is superior to other seven well-known heuristic algorithms.

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Acknowledgments

This work is supported by National Natural Science Foundation of China (61972184, 61562032, 61662027, 61762042); Modern Agricultural Research Collaborative Innovation Project of Jiangxi (JXXTCXQN201906); Special Fund Project for Graduate Innovation of Jiangxi (YC2017-B065)

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Authors and Affiliations

  1. School of Information Engineering, Nanchang University, Nanchang, 330031, China

    Longzhen Duan & Shuqing Yang

  2. School of Software, Jiangxi University of Science and Technology, Nanchang, 330013, China

    Shuqing Yang

  3. Guangdong Key Laboratory of Modern Control Technology, Guangdong Institute of Intelligent Manufacturing, Guangzhou, 510070, China

    Dongbo Zhang

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  1. Longzhen Duan
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  2. Shuqing Yang
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  3. Dongbo Zhang
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Correspondence to Shuqing Yang.

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Duan, L., Yang, S. & Zhang, D. Multilevel thresholding using an improved cuckoo search algorithm for image segmentation. J Supercomput 77, 6734–6753 (2021). https://doi.org/10.1007/s11227-020-03566-7

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