Lévy flight and Chaos theory based metaheuristics for grayscale image thresholding
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2023
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Abstract
The Levy flight and Chaos theory-based Gravitational Search Algorithm (LCGSA) has been applied for the image segmentation task. In LCGSA, the exploration is carried out by levy flight, while exploitation is guaranteed by chaotic maps. Besides, Kapur’s entropy method has been utilized to segment the sample image into various regions based on pixel concentration. Two famous benchmark images namely Cameraman and Lena have been considered for evaluating the segmentation capability of different LCGSA versions. Various performance metrics like standard deviation (SD), mean square error (MSE), structural similarity index measure (SSIM), feature similarity index measure (FSIM), etc. have been employed to validate the optimization performance of LCGSA. Moreover, the signed Wilcoxon rank-sum test has been applied to statistically verify the simulation results. Furthermore, eight state-of-the-art heuristic algorithms have been considered for comparative analysis. The MATLAB codes of the work will be publicly available on the author’s GitHub page, that is, https://github.com/SajadAHMAD1 and MathWorks website, https://www.mathworks.com/matlabcentral/profile/authors/6240015. © 2023 Elsevier Inc. All rights reserved.