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Journal of Bionic Engineering

, Volume 16, Issue 5, pp 954–964 | Cite as

Multilevel Image Thresholding Using Tsallis Entropy and Cooperative Pigeon-inspired Optimization Bionic Algorithm

  • Yun Wang
  • Guangbin ZhangEmail author
  • Xiaofeng Zhang
Article
  • 1 Downloads

Abstract

Multilevel thresholding is a simple and effective method in numerous image segmentation applications. In this paper, we propose a new multilevel thresholding method that uses cooperative pigeon-inspired optimization algorithm with dynamic distance threshold (CPIOD) for boosting applicability and the practicality of the optimum thresholding techniques. Firstly, we employ the cooperative behavior in the map and compass operator of the pigeon-inspired optimization algorithm to overcome the “curse of dimensionality” and help the algorithm converge fast. Then, a distance threshold is added to maintain the diversity of the pigeon population and increase the vitality to avoid local optimization. Tsallis entropy is used as the objective function to evaluate the optimum thresholds for the considered gray scale images. Four benchmark images are applied to test the property and the stability of the proposed CPIOD algorithm and three other optimization algorithms in multilevel thresholding problems. Segmentation results of four optimization algorithms show that CPIOD algorithm can not only get higher quality segmentation results, but also has better stability.

Keywords

bionic algorithm multilevel thresholding Tsallis entropy pigeon-inspired optimization image segmentation 

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Notes

Acknowledgement

This work was supported by the National Natural Science Foundation of China (Grant Nos. 11574191 and 11674208).

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Copyright information

© Jilin University 2019

Authors and Affiliations

  1. 1.School of Physics and Information TechnologyShaanxi Normal UniversityXi’anChina

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