Publication:
A Comparative Study of PCA and LBP for Face Recognition under Illumination Variations [Farkli Aydinlatmalarda Yüz Tanima için PCA ve LBP'nin Karşilaştirilmasi]

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dc.contributor.authorsErol M.K., Kapan U.A., Ozturk M.K., Uslu B.C., Bas A.
dc.date.accessioned2022-03-15T02:15:02Z
dc.date.accessioned2026-01-10T17:53:55Z
dc.date.available2022-03-15T02:15:02Z
dc.date.issued2020
dc.description.abstractChanges in lighting conditions are an important factor for facial recognition applications. The algorithms used in these applications have various approaches and are directly affected by environments under difficult lighting settings. In this study, we investigate two appearance-based local and global approaches, namely Principal Component Analysis and Local Binary Patterns algorithms, examine important studies on these algorithms and compare their facial recognition performances on images from the Extended Yale Face Database B. Experiments show that the LBP method provides better results under varying lighting conditions. © 2020 IEEE.
dc.identifier.doi10.1109/ASYU50717.2020.9259856
dc.identifier.isbn9781728191362
dc.identifier.urihttps://hdl.handle.net/11424/248091
dc.language.isotur
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.ispartofProceedings - 2020 Innovations in Intelligent Systems and Applications Conference, ASYU 2020
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectfacial recognition
dc.subjectfeature extraction
dc.subjectlighting
dc.subjectlocal binary patterns
dc.subjectprincipal component analysis
dc.titleA Comparative Study of PCA and LBP for Face Recognition under Illumination Variations [Farkli Aydinlatmalarda Yüz Tanima için PCA ve LBP'nin Karşilaştirilmasi]
dc.typeconferenceObject
dspace.entity.typePublication
oaire.citation.titleProceedings - 2020 Innovations in Intelligent Systems and Applications Conference, ASYU 2020

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