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dc.contributor.authorKoç, Mehmet
dc.contributor.authorBarkana, Atalay
dc.date.accessioned2019-10-21T20:12:05Z
dc.date.available2019-10-21T20:12:05Z
dc.date.issued2011
dc.identifier.issn0096-3003
dc.identifier.urihttps://dx.doi.org/10.1016/j.amc.2011.05.048
dc.identifier.urihttps://hdl.handle.net/11421/20396
dc.descriptionWOS: 000291680400052en_US
dc.description.abstractFisher linear discriminant analysis (FLDA) is a very popular method in face recognition. But FLDA fails when one image per person is available. This is due to the fact that the within-class scatter matrices cannot be calculated. An image decomposition method that uses QR-decomposition with column pivoting (QRCP) is proposed in this paper to overcome one image per person problem. At first, the image and its two approximations that are evaluated using QRCP-decomposition are all placed in the training set. Then 2D-FLDA method becomes applicable with these new data. The performance of the proposed image decomposition algorithm is tested on five different face databases, namely ORL, FERET, YALE, UMIST, and PolyU-NIR using 2D-FLDA. Our image decomposition algorithm performs better than the SVD based method mentioned by Gao et al. (2008) [1] in terms of recognition rate and training time in all of the above databasesen_US
dc.description.sponsorshipDOD Counterdrug Technology Development Program Officeen_US
dc.description.sponsorshipPortions of the research in this paper use the FERET database of facial images collected under the FERET program, sponsored by the DOD Counterdrug Technology Development Program Office.en_US
dc.language.isoengen_US
dc.publisherElsevier Science Incen_US
dc.relation.isversionof10.1016/j.amc.2011.05.048en_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectOne Sample Problemen_US
dc.subjectFace Recognitionen_US
dc.subjectFisher Linear Discriminant Analysisen_US
dc.subjectQrcp-Decompositionen_US
dc.subjectSingular Value Decompositionen_US
dc.subjectVirtual Face Imageen_US
dc.titleA new solution to one sample problem in face recognition using FLDAen_US
dc.typearticleen_US
dc.relation.journalApplied Mathematics and Computationen_US
dc.contributor.departmentAnadolu Üniversitesi, Mühendislik Fakültesi, Elektrik ve Elektronik Mühendisliği Bölümüen_US
dc.identifier.volume217en_US
dc.identifier.issue24en_US
dc.identifier.startpage10368en_US
dc.identifier.endpage10376en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.contributor.institutionauthorBarkana, Atalay


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