Weighting and Classification of Image Features using Optimization Algorithms

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dc.contributor.authorOzturk, Saban
dc.contributor.authorOzkaya, Umut
dc.contributor.authorAkdemir, Bayram
dc.contributor.authorSeyfi, Levent
dc.date.accessioned2020-03-26T20:11:40Z
dc.date.available2020-03-26T20:11:40Z
dc.date.issued2018
dc.departmentSelçuk Üniversitesien_US
dc.descriptionInternational Symposium on Fundamentals of Electrical Engineering (ISFEE) -- NOV 01-03, 2018 -- Univ Politehnica Bucharest, Fac Elect Engn, Elect Engn Dept, Bucharest, ROMANIAen_US
dc.description.abstractIn this study, importance ratios of features extracted from images using feature extraction algorithms are examined. A significance coefficient is determined for each feature parameter. The number of features is reduced according to the weight of the importance calculated for each feature. The classification success is examined for each case. Firstly, six feature extraction algorithms are used for this purpose. The classification success of all these feature extraction algorithms has been examined separately. Then, all properties are combined to form a single property matrix. The obtained property matrix is reduced by using principal component analysis and relieff methods. New feature matrices provide increased classification performance. However, it is inefficient to classify a high number of properties in real-time applications. To overcome this problem, the effect of classifying each parameter in the property matrix is examined and the insignificant properties are discarded. The proposed method is tested using histopathological images. Histopathological images are divided into 4 separate classes. The proposed method reduces the raw feature matrix by 50% with 97.2% classification success.en_US
dc.description.sponsorshipAssoc Romanian Elect Elect Engineers, IEEE Romania Sect CAS CS Chapter, IEEEen_US
dc.identifier.isbn978-1-5386-7212-9
dc.identifier.scopusqualityN/Aen_US
dc.identifier.urihttps://hdl.handle.net/20.500.12395/37132
dc.identifier.wosWOS:000480396400072en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.ispartof2018 INTERNATIONAL SYMPOSIUM ON FUNDAMENTALS OF ELECTRICAL ENGINEERING (ISFEE)en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectfeature extractionen_US
dc.subjectclassificationen_US
dc.subjecthistopathological imageen_US
dc.subjectpcaen_US
dc.subjectrelieffen_US
dc.titleWeighting and Classification of Image Features using Optimization Algorithmsen_US
dc.typeConference Objecten_US

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