A Logistic Chaotic Barnacles Mating Optimizer With Masi Entropy for Color Image Multilevel Thresholding Segmentation

Barnacles mating optimizer (BMO) is an evolutionary algorithm that simulates the mating and reproductive behavior of barnacle population. In this article, an improved Barnacles mating optimizer based on logistic model and chaotic map (LCBMO) was proposed to produce the high-quality optimal result. F...

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Bibliographic Details
Published in:IEEE access 2020, Vol.8, p.213130-213153
Main Authors: Li, Hongbo, Zheng, Gang, Sun, Kangjian, Jiang, Zichao, Li, Yao, Jia, Heming
Format: Article
Language:English
Subjects:
Algorithms
Barnacles mating optimizer
chaotic map
Color
color image segmentation
Color imagery
Convergence
Entropy
Evolutionary algorithms
Exploitation
Image segmentation
Linear programming
logistic model
Logistics
Masi entropy
Multilevel
multilevel thresholding
Optimization
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Summary:Barnacles mating optimizer (BMO) is an evolutionary algorithm that simulates the mating and reproductive behavior of barnacle population. In this article, an improved Barnacles mating optimizer based on logistic model and chaotic map (LCBMO) was proposed to produce the high-quality optimal result. Firstly, the logistic model is introduced into the native BMO to realize the automatic conversion parameters. This strategy maintains a proper relationship between exploitation and exploration. Then, the chaotic map is integrated to enhance the exploitation capability of the algorithm. After that, six variants based on LCBMO are compared to find the best algorithm on benchmark functions. Moreover, to the knowledge of the authors, there is no previous study on this algorithm for multilevel color image segmentation. LCBMO takes Masi entropy as the objective function to find the optimal threshold. By comparing different thresholds, different types of images, different optimization algorithms, and different objective functions, our proposed technique is reliable and promising in solving color image multilevel thresholding segmentation. Wilcoxon rank-sum test and Friedman test also prove that the simulation results are statistically significant.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2020.3040177