Fuzzy Multilevel Image Thresholding Based on Improved Coyote Optimization Algorithm

Due to the computational complexity of multilevel image thresholding, Swarm Intelligence Optimization Algorithm (SIOA) has been widely applied to improve the calculation efficiency. Therefore, more and more attention has been paid to exploring the application of the latest SIOA in multilevel segment...

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Autores principales:	Linguo Li, Lijuan Sun, Yu Xue, Shujing Li, Xuwen Huang, Romany Fouad Mansour
Formato:	article
Lenguaje:	EN
Publicado:	IEEE 2021
Materias:	Coyote optimization algorithm information entropy image segmentation multilevel thresholding Electrical engineering. Electronics. Nuclear engineering TK1-9971
Acceso en línea:	https://doaj.org/article/a2959c73dd4744a4a83d1443f7ef35dc
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id	oai:doaj.org-article:a2959c73dd4744a4a83d1443f7ef35dc
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spelling	oai:doaj.org-article:a2959c73dd4744a4a83d1443f7ef35dc2021-11-19T00:05:36ZFuzzy Multilevel Image Thresholding Based on Improved Coyote Optimization Algorithm2169-353610.1109/ACCESS.2021.3060749https://doaj.org/article/a2959c73dd4744a4a83d1443f7ef35dc2021-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9359752/https://doaj.org/toc/2169-3536Due to the computational complexity of multilevel image thresholding, Swarm Intelligence Optimization Algorithm (SIOA) has been widely applied to improve the calculation efficiency. Therefore, more and more attention has been paid to exploring the application of the latest SIOA in multilevel segmentation. This article takes Otsu and fuzzy entropy as the objective functions, using Coyote Optimization Algorithm (COA) for multilevel thresholds optimization selection, through fuzzy median aggregation of local neighborhood information and then forms the Fuzzy Coyote Optimization Algorithm (FCOA), so that the thresholding image segmentation can be achieved in the end. To prevent the COA algorithm from falling into the local optimum, this article follows the differential evolution strategy adopted by the standard COA, using the number of iterations to construct the differential scaling factor to form the Improved Coyote Optimization Algorithm (ICOA). The experimental results show that fuzzy Kapur entropy and fuzzy median value aggregation-based ICOA(FICOA) achieves better image segmentation quality. Compared with Grey Wolf Optimizer (GWO), Fuzzy Modified Quick Artificial Bee Colony and Aggregation Algorithm (FMQABCA) and Fuzzy Modified Discrete Grey Wolf Optimizer and Aggregation Algorithm (FMDGWOA), FCOA and FICOA have certain advantages in visual effects of image segmentation and PSNR, FSIM evaluation indices. Particularly compared with GWO (also a wolf evolutionary algorithm), FICOA shows significant advantages.Linguo LiLijuan SunYu XueShujing LiXuwen HuangRomany Fouad MansourIEEEarticleCoyote optimization algorithminformation entropyimage segmentationmultilevel thresholdingElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENIEEE Access, Vol 9, Pp 33595-33607 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Coyote optimization algorithm information entropy image segmentation multilevel thresholding Electrical engineering. Electronics. Nuclear engineering TK1-9971
spellingShingle	Coyote optimization algorithm information entropy image segmentation multilevel thresholding Electrical engineering. Electronics. Nuclear engineering TK1-9971 Linguo Li Lijuan Sun Yu Xue Shujing Li Xuwen Huang Romany Fouad Mansour Fuzzy Multilevel Image Thresholding Based on Improved Coyote Optimization Algorithm
description	Due to the computational complexity of multilevel image thresholding, Swarm Intelligence Optimization Algorithm (SIOA) has been widely applied to improve the calculation efficiency. Therefore, more and more attention has been paid to exploring the application of the latest SIOA in multilevel segmentation. This article takes Otsu and fuzzy entropy as the objective functions, using Coyote Optimization Algorithm (COA) for multilevel thresholds optimization selection, through fuzzy median aggregation of local neighborhood information and then forms the Fuzzy Coyote Optimization Algorithm (FCOA), so that the thresholding image segmentation can be achieved in the end. To prevent the COA algorithm from falling into the local optimum, this article follows the differential evolution strategy adopted by the standard COA, using the number of iterations to construct the differential scaling factor to form the Improved Coyote Optimization Algorithm (ICOA). The experimental results show that fuzzy Kapur entropy and fuzzy median value aggregation-based ICOA(FICOA) achieves better image segmentation quality. Compared with Grey Wolf Optimizer (GWO), Fuzzy Modified Quick Artificial Bee Colony and Aggregation Algorithm (FMQABCA) and Fuzzy Modified Discrete Grey Wolf Optimizer and Aggregation Algorithm (FMDGWOA), FCOA and FICOA have certain advantages in visual effects of image segmentation and PSNR, FSIM evaluation indices. Particularly compared with GWO (also a wolf evolutionary algorithm), FICOA shows significant advantages.
format	article
author	Linguo Li Lijuan Sun Yu Xue Shujing Li Xuwen Huang Romany Fouad Mansour
author_facet	Linguo Li Lijuan Sun Yu Xue Shujing Li Xuwen Huang Romany Fouad Mansour
author_sort	Linguo Li
title	Fuzzy Multilevel Image Thresholding Based on Improved Coyote Optimization Algorithm
title_short	Fuzzy Multilevel Image Thresholding Based on Improved Coyote Optimization Algorithm
title_full	Fuzzy Multilevel Image Thresholding Based on Improved Coyote Optimization Algorithm
title_fullStr	Fuzzy Multilevel Image Thresholding Based on Improved Coyote Optimization Algorithm
title_full_unstemmed	Fuzzy Multilevel Image Thresholding Based on Improved Coyote Optimization Algorithm
title_sort	fuzzy multilevel image thresholding based on improved coyote optimization algorithm
publisher	IEEE
publishDate	2021
url	https://doaj.org/article/a2959c73dd4744a4a83d1443f7ef35dc
work_keys_str_mv	AT linguoli fuzzymultilevelimagethresholdingbasedonimprovedcoyoteoptimizationalgorithm AT lijuansun fuzzymultilevelimagethresholdingbasedonimprovedcoyoteoptimizationalgorithm AT yuxue fuzzymultilevelimagethresholdingbasedonimprovedcoyoteoptimizationalgorithm AT shujingli fuzzymultilevelimagethresholdingbasedonimprovedcoyoteoptimizationalgorithm AT xuwenhuang fuzzymultilevelimagethresholdingbasedonimprovedcoyoteoptimizationalgorithm AT romanyfouadmansour fuzzymultilevelimagethresholdingbasedonimprovedcoyoteoptimizationalgorithm
_version_	1718420684941557760

Fuzzy Multilevel Image Thresholding Based on Improved Coyote Optimization Algorithm

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