A fuzzy image clustering method based on an improved backtracking search optimization algorithm with an inertia weight parameter

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dc.contributor.authorToz, Güliz
dc.contributor.authorYücedağ, İbrahim
dc.contributor.authorErdoğmuş, Pakize
dc.date.accessioned2020-04-30T22:38:40Z
dc.date.available2020-04-30T22:38:40Z
dc.date.issued2019
dc.departmentDÜ, Teknoloji Fakültesi, Bilgisayar Mühendisliği Bölümüen_US
dc.descriptionWOS: 000474400800003en_US
dc.description.abstractIn this paper, we introduced a novel image clustering method based on combination of the classical Fuzzy C-Means (FCM) algorithm and Backtracking Search optimization Algorithm (BSA). The image clustering was achieved by minimizing the objective function of FCM with BSA. In order to improve the local search ability of the new algorithm, an inertia weight parameter (w) was proposed for BSA. The improvement was accomplished by using w in the steps of the determination of the search-direction matrix of BSA and the new algorithm was named as w-BSAFCM. In order to show the effectiveness of the new algorithm, FCM was also combined with the general forms of BSA in the same manner and three benchmark images were clustered by utilizing these algorithms. The obtained results were analyzed according to the objective function and Davies-Bouldin index values to compare the performances of the algorithms. According to the results, it was shown that w-BSAFCM can be effectively be used for solving image clustering problem. (C) 2018 The Authors. Production and hosting by Elsevier B.V. on behalf of King Saud University.en_US
dc.identifier.doi10.1016/j.jksuci.2018.02.011en_US
dc.identifier.endpage303en_US
dc.identifier.issn1319-1578
dc.identifier.issn2213-1248
dc.identifier.issue3en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage295en_US
dc.identifier.urihttps://doi.org/10.1016/j.jksuci.2018.02.011
dc.identifier.urihttps://hdl.handle.net/20.500.12684/2353
dc.identifier.volume31en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherElsevier Science Bven_US
dc.relation.ispartofJournal Of King Saud University-Computer And Information Sciencesen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectBSAen_US
dc.subjectFCMen_US
dc.subjectImage clusteringen_US
dc.titleA fuzzy image clustering method based on an improved backtracking search optimization algorithm with an inertia weight parameteren_US
dc.typeArticleen_US

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