Computer Science ›› 2016, Vol. 43 ›› Issue (7): 89-94.doi: 10.11896/j.issn.1002-137X.2016.07.015

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Improved Bacterial Foraging Optimization Algorithm Used for Multi-level Threshold Segmentation Based on Exponent Entropy

ZHANG Xin-ming, TU Qiang and LIU Yan   

  • Online:2018-12-01 Published:2018-12-01

Abstract: In view of the characteristics of ordered positive integer programming of multi-level segmentation methods,an improved bacterial foraging optimization(IBFO) algorithm used for multi-level threshold segmentation based on exponent entropy was proposed in this paper.Firstly,a chemotactic step mechanism of the standard bacterial foraging optimization(SBFO) algorithm is changed into a dynamic chemotactic step approach to improve self-adaptation.Secondly,the original elimination-dispersal operator is replaced with a new one based on combining random mutation and dynamical local mutation,and the random mutation is used in the first phase to enhance the global search ability and the dynamical mutation is used in the second phase to improve local search performance.Thirdly,the communication mechanism of SBFO is abandoned to accelerate the running speed of the algorithm.Finally,IBFO is further modified to fit for the multi-level threshold segmentation based on exponent entropy.Experimental results show that the proposed method has better optimization performance with less computation time compared to SBFO,MBFO and IPSO.

Key words: Image segmentation,Multi-level threshold segmentation,Bacterial foraging optimization algorithm,Exponent entropy

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