A Grouping Differential Evolution Algorithm Boosted by Attraction and Repulsion Strategies for Masi Entropy-Based Multi-Level Image Segmentation

Mousavirad, Seyed Jalaleddin; Zabihzadeh, Davood; Oliva, Diego; Perez-Cisneros, Marco; Schaefer, Gerald

doi:10.3390/e24010008

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A Grouping Differential Evolution Algorithm Boosted by Attraction and Repulsion Strategies for Masi Entropy-Based Multi-Level Image Segmentation

Seyed Jalaleddin Mousavirad

^1,*,

Davood Zabihzadeh

Diego Oliva

^2,*

Marco Perez-Cisneros

^2,*

and

Gerald Schaefer

Computer Engineering Department, Hakim Sabzevari University, Sabzevar 96179-76487, Iran

Departamento de Innovación Basada en la Información y el Conocimiento, Universidad de Guadalajara, CUCEI, Guadalajara 44430, Mexico

Department of Computer Science, Loughborough University, Loughborough LE11 3TT, UK

Authors to whom correspondence should be addressed.

Academic Editor: Amelia Carolina Sparavigna

Entropy 2022, 24(1), 8; https://doi.org/10.3390/e24010008

Received: 21 November 2021 / Revised: 14 December 2021 / Accepted: 15 December 2021 / Published: 21 December 2021

(This article belongs to the Special Issue Entropy in Soft Computing and Machine Learning Algorithms)

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Abstract

Masi entropy is a popular criterion employed for identifying appropriate threshold values in image thresholding. However, with an increasing number of thresholds, the efficiency of Masi entropy-based multi-level thresholding algorithms becomes problematic. To overcome this, we propose a novel differential evolution (DE) algorithm as an effective population-based metaheuristic for Masi entropy-based multi-level image thresholding. Our ME-GDEAR algorithm benefits from a grouping strategy to enhance the efficacy of the algorithm for which a clustering algorithm is used to partition the current population. Then, an updating strategy is introduced to include the obtained clusters in the current population. We further improve the algorithm using attraction (towards the best individual) and repulsion (from random individuals) strategies. Extensive experiments on a set of benchmark images convincingly show ME-GDEAR to give excellent image thresholding performance, outperforming other metaheuristics in 37 out of 48 cases based on cost function evaluation, 26 of 48 cases based on feature similarity index, and 20 of 32 cases based on Dice similarity. The obtained results demonstrate that population-based metaheuristics can be successfully applied to entropy-based image thresholding and that strengthening both exploitation and exploration strategies, as performed in ME-GDEAR, is crucial for designing such an algorithm. View Full-Text

Keywords: image segmentation; multi-level image thresholding; optimisation; differential evolution; clustering

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Mousavirad, S.J.; Zabihzadeh, D.; Oliva, D.; Perez-Cisneros, M.; Schaefer, G. A Grouping Differential Evolution Algorithm Boosted by Attraction and Repulsion Strategies for Masi Entropy-Based Multi-Level Image Segmentation. Entropy 2022, 24, 8. https://doi.org/10.3390/e24010008

AMA Style

Mousavirad SJ, Zabihzadeh D, Oliva D, Perez-Cisneros M, Schaefer G. A Grouping Differential Evolution Algorithm Boosted by Attraction and Repulsion Strategies for Masi Entropy-Based Multi-Level Image Segmentation. Entropy. 2022; 24(1):8. https://doi.org/10.3390/e24010008

Chicago/Turabian Style

Mousavirad, Seyed J., Davood Zabihzadeh, Diego Oliva, Marco Perez-Cisneros, and Gerald Schaefer. 2022. "A Grouping Differential Evolution Algorithm Boosted by Attraction and Repulsion Strategies for Masi Entropy-Based Multi-Level Image Segmentation" Entropy 24, no. 1: 8. https://doi.org/10.3390/e24010008

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Author Biographies

Seyed Jalaleddin Mousavirad

Seyed Jalaleddin Mousavirad completed his Ph.D. in Computer Engineering, Artificial Intelligence at the University of Kashan, Iran. He worked at the University of Tehran (2018⁠–2019), in the School of Computer Engineering, Azad University (2019⁠–2020), in the School of Engineering, before joining the Faculty of Engineering at Hakim Sabzevari University. He has an outstanding research record and significant capabilities in the area of pattern recognition and machine learning, image processing, and evolutionary computation. He has published 6 book chapters and more than 75 papers in reputable academic journals and conferences. He has also visited a world-class research group of Xi’an Jiaotong⁠–Liverpool University, China. He is an active reviewer for more than 35 prestigious journals and conferences such as IEEE Transactions on Evolutionary Computation, IEEE Transactions Systems, Mans, and Cybernetics, IEEE Transactions on Cybernetics, IEEE Access, IEEE System Journal, Expert Systems with Applications, Applied Soft Computing, Soft Computing, Swarm and Evolutionary Computation, Information Sciences, and Connection Science.

Diego Oliva

Diego Oliva received his B.S. degree in Electronics and Computer Engineering from the Industrial Technical Education Center (CETI) of Guadalajara, Mexico, in 2007, his M.Sc. degree in Electronic Engineering and Computer Sciences from the University of Guadalajara, Mexico, in 2010, and completed his Ph.D. in Informatics at the Complutense University of Madrid in 2015. Currently, he is an associate professor at the University of Guadalajara in Mexico. His current research interests include computer vision, image processing, artificial intelligence, and metaheuristic optimization algorithms.

Gerald Schaefer

Gerald Schaefer completed his Ph.D. in Computer Vision at the University of East Anglia. He worked at the Colour & Imaging Institute, of the University of Derby (1997⁠–1999), in the School of Information Systems, of the University of East Anglia (2000⁠–2001), in the School of Computing and Informatics at Nottingham Trent University (2001-2006), and in the School of Engineering and Applied Science of Aston University (2006⁠–2009) before joining the Department of Computer Science at Loughborough University where he leads the Vision, Imaging and Autonomous Systems Research Group. His research interests are mainly in the areas of colour image analysis, image retrieval, physics-based vision, medical imaging, and computational intelligence. He has published extensively in these areas with a total publication count exceeding 300. He has been invited as a keynote or tutorial speaker to numerous conferences, is the organiser of various international workshops and special sessions at conferences, and the editor of several books, conference proceedings and special journal issues. He is a member of the editorial board of more than 10 international journals, reviews for over 80 journals, and served on the programme committee of more than 200 conferences.

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A Grouping Differential Evolution Algorithm Boosted by Attraction and Repulsion Strategies for Masi Entropy-Based Multi-Level Image Segmentation

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