A COMPARISON OF EIGENVALUE METHODS FOR PRINCIPAL COMPONENT ANALYSIS

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dc.contributor.authorDanisman, Y.
dc.contributor.authorYilmaz, M. F.
dc.contributor.authorOzkaya, A.
dc.contributor.authorComlekciler, I. T.
dc.date.accessioned2020-03-26T18:49:07Z
dc.date.available2020-03-26T18:49:07Z
dc.date.issued2014
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractWe compare four commonly used eigenvector methods, namely cyclic Jacobi's method of iteration, Wiedlandt's deflation, Hotel ling's deflation, and MATLAB's own eigenvalue method for the success of face recognition which is based on Principal Component Analysis (PCA). We report that the highest recognition rate is equally achieved by MATLAB's eigenvalue method and Hotel ling's deflation. The former is observed to be the fastest for large numbers of dominant eigenfaces while scaling the best with the number of computational cores. On the other hand, the latter has a brief and open source code that can be easily modified for a given purpose. We further investigate the impact of altering face images to improve the recognition rate. Different sets of images have been obtained from two well-known face databases, various effects using imaging filters have been applied to them, and the resulting sets have been used as both training and test sets. Recognition rates reveal that some of these filtered sets can be even better candidates for training and testing than the original sets.en_US
dc.identifier.endpage331en_US
dc.identifier.issn1683-3511en_US
dc.identifier.issn1683-6154en_US
dc.identifier.issue3en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage316en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12395/30531
dc.identifier.volume13en_US
dc.identifier.wosWOS:000344830000004en_US
dc.identifier.wosqualityQ4en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherMINISTRY COMMUNICATIONS & HIGH TECHNOLOGIES REPUBLIC AZERBAIJANen_US
dc.relation.ispartofAPPLIED AND COMPUTATIONAL MATHEMATICSen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectPCAen_US
dc.subjectHotel lingen_US
dc.subjectWielandten_US
dc.subjectJacobien_US
dc.subjectPattern Recognitionen_US
dc.subjectFace Recognitionen_US
dc.titleA COMPARISON OF EIGENVALUE METHODS FOR PRINCIPAL COMPONENT ANALYSISen_US
dc.typeArticleen_US

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