Kapur's entropy for multilevel thresholding image segmentation based on moth-flame optimization

Multilevel thresholding is a reliable and efficacious method for image segmentation that has recently received widespread recognition. However, the computational complexity of the multilevel thresholding method increases as the threshold level increases, which causes the low segmentation accuracy of...

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Autores principales:	Wenqi Ji, Xiaoguang He
Formato:	article
Lenguaje:	EN
Publicado:	AIMS Press 2021
Materias:	multilevel thresholding image segmentation moth-flame optimization kapur's entropy Biotechnology TP248.13-248.65 Mathematics QA1-939
Acceso en línea:	https://doaj.org/article/d2e709ae733049beaecd49ed214d7510
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id	oai:doaj.org-article:d2e709ae733049beaecd49ed214d7510
record_format	dspace
spelling	oai:doaj.org-article:d2e709ae733049beaecd49ed214d75102021-11-23T01:42:51ZKapur's entropy for multilevel thresholding image segmentation based on moth-flame optimization10.3934/mbe.20213531551-0018https://doaj.org/article/d2e709ae733049beaecd49ed214d75102021-08-01T00:00:00Zhttps://www.aimspress.com/article/doi/10.3934/mbe.2021353?viewType=HTMLhttps://doaj.org/toc/1551-0018Multilevel thresholding is a reliable and efficacious method for image segmentation that has recently received widespread recognition. However, the computational complexity of the multilevel thresholding method increases as the threshold level increases, which causes the low segmentation accuracy of this method. To overcome this shortcoming, this paper presents a moth-flame optimization (MFO) established on Kapur's entropy to clarify the multilevel thresholding image segmentation. The MFO adjusts exploration and exploitation to achieve the best fitness value. To validate the overall performance, MFO is compared with other algorithms to realize the global optimal solution to maximize the target value of Kapur's entropy. Some critical evaluation indicators are used to determine the segmentation effect and optimization performance of each algorithm. The experimental results indicate that MFO has a faster convergence speed, higher calculation accuracy, better segmentation effect and better stability.Wenqi Ji Xiaoguang HeAIMS Pressarticlemultilevel thresholdingimage segmentationmoth-flame optimizationkapur's entropyBiotechnologyTP248.13-248.65MathematicsQA1-939ENMathematical Biosciences and Engineering, Vol 18, Iss 6, Pp 7110-7142 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	multilevel thresholding image segmentation moth-flame optimization kapur's entropy Biotechnology TP248.13-248.65 Mathematics QA1-939
spellingShingle	multilevel thresholding image segmentation moth-flame optimization kapur's entropy Biotechnology TP248.13-248.65 Mathematics QA1-939 Wenqi Ji Xiaoguang He Kapur's entropy for multilevel thresholding image segmentation based on moth-flame optimization
description	Multilevel thresholding is a reliable and efficacious method for image segmentation that has recently received widespread recognition. However, the computational complexity of the multilevel thresholding method increases as the threshold level increases, which causes the low segmentation accuracy of this method. To overcome this shortcoming, this paper presents a moth-flame optimization (MFO) established on Kapur's entropy to clarify the multilevel thresholding image segmentation. The MFO adjusts exploration and exploitation to achieve the best fitness value. To validate the overall performance, MFO is compared with other algorithms to realize the global optimal solution to maximize the target value of Kapur's entropy. Some critical evaluation indicators are used to determine the segmentation effect and optimization performance of each algorithm. The experimental results indicate that MFO has a faster convergence speed, higher calculation accuracy, better segmentation effect and better stability.
format	article
author	Wenqi Ji Xiaoguang He
author_facet	Wenqi Ji Xiaoguang He
author_sort	Wenqi Ji
title	Kapur's entropy for multilevel thresholding image segmentation based on moth-flame optimization
title_short	Kapur's entropy for multilevel thresholding image segmentation based on moth-flame optimization
title_full	Kapur's entropy for multilevel thresholding image segmentation based on moth-flame optimization
title_fullStr	Kapur's entropy for multilevel thresholding image segmentation based on moth-flame optimization
title_full_unstemmed	Kapur's entropy for multilevel thresholding image segmentation based on moth-flame optimization
title_sort	kapur's entropy for multilevel thresholding image segmentation based on moth-flame optimization
publisher	AIMS Press
publishDate	2021
url	https://doaj.org/article/d2e709ae733049beaecd49ed214d7510
work_keys_str_mv	AT wenqiji kapursentropyformultilevelthresholdingimagesegmentationbasedonmothflameoptimization AT xiaoguanghe kapursentropyformultilevelthresholdingimagesegmentationbasedonmothflameoptimization
_version_	1718417404717957120

Kapur's entropy for multilevel thresholding image segmentation based on moth-flame optimization

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