D-MOSG: Discrete multi-objective shuffled gray wolf optimizer for multi-level image thresholding

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dc.contributor.authorKarakoyun, Murat
dc.contributor.authorGulcu, Saban
dc.contributor.authorKodaz, Halife
dc.date.accessioned2024-02-23T14:12:48Z
dc.date.available2024-02-23T14:12:48Z
dc.date.issued2021
dc.departmentNEÜen_US
dc.description.abstractSegmentation is an important step of image processing that directly affects its success. Among the methods used for image segmentation, histogram-based thresholding is a very popular approach. To apply the thresholding approach, many methods such as Otsu, Kapur, Renyi etc. have been proposed in order to produce the thresholds that will segment the image optimally. These suggested methods usually have their own characteristics and are successful for particular images. It can be thought that better results may be obtained by using objective functions with different characteristics together. In this study, the thresholding which is originally applied as a single-objective problem has been considered as a multi-objective problem by using the Otsu and Kapur methods. Therefore, the discrete multi-objective shuffled gray wolf optimizer (D-MOSG) algorithm has been proposed for multi-level thresholding segmentation. Experiments have clearly shown that the D-MOSG algorithm has achieved superior results than the compared algorithms. (C) 2021 Karabuk University. Publishing services by Elsevier B.V.en_US
dc.identifier.doi10.1016/j.jestch.2021.03.011
dc.identifier.endpage1466en_US
dc.identifier.issn2215-0986
dc.identifier.issue6en_US
dc.identifier.scopus2-s2.0-85103966023en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage1455en_US
dc.identifier.urihttps://doi.org/10.1016/j.jestch.2021.03.011
dc.identifier.urihttps://hdl.handle.net/20.500.12452/12195
dc.identifier.volume24en_US
dc.identifier.wosWOS:000707779000016en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherElsevier - Division Reed Elsevier India Pvt Ltden_US
dc.relation.ispartofEngineering Science And Technology-An International Journal-Jestechen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectMulti-Level Thresholdingen_US
dc.subjectImage Segmentationen_US
dc.subjectMulti-Objective Optimizationen_US
dc.subjectShuffled Frog Leapingen_US
dc.subjectGray Wolf Optimizeren_US
dc.titleD-MOSG: Discrete multi-objective shuffled gray wolf optimizer for multi-level image thresholdingen_US
dc.typeArticleen_US

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