Face recognition based on multi features extractors

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dc.contributor.authorAlAzzawi, Abdulbasit
dc.contributor.authorUçan, Osman Nuri
dc.contributor.authorBayat, Oğuz
dc.date.accessioned2021-05-15T12:36:52Z
dc.date.available2021-05-15T12:36:52Z
dc.date.issued2017
dc.departmentMühendislik ve Doğa Bilimleri Fakültesi, Elektrik ve Bilgisayar Mühendisliği Bölümüen_US
dc.descriptionInternational Conference on Engineering and Technology (ICET) -- AUG 21-23, 2017 -- Akdeniz Univ, Antalya, TURKEY
dc.description.abstractFace recognition is the core application in the biometric technology area. It is widely used in the advanced application of robotics and computer vision. Raising commercial of face recognition and low enforcement makes a request of it increases in the last decade. In this paper, we present state of the art of in face recognition technologies by focusing on some traditional issues and some techniques to treats these problems. The advantage of suggested algorithm is to solve the popular issues in face recognition such as light conditions and environmental factors that lead to the low-performance. In proposed algorithm, groups of edge detection filters (Sobel, Prewitt, and Roberts) were used to extract edges of the faces in images. First derivative edge detection filters were performed to get best features of data set. moreover, using edge detection process that used by first order filter is to reduce data as much as possible by removing image background. The new method used as feature extractor addition to traditional PCA. Gathering features by using slope method and PCA is to find the optimal faces vectors as the inputs to the classifier (NNMLP neural network). Results have revealed acceptable correct classification. As data test set we used BIO-ID data base in the proposed system.en_US
dc.description.sponsorshipIARES, IEEEen_US
dc.identifier.isbn978-1-5386-1949-0
dc.identifier.issn2380-9345
dc.identifier.scopus2-s2.0-85047869866
dc.identifier.scopusqualityN/A
dc.identifier.urihttps://hdl.handle.net/20.500.12939/423
dc.identifier.wosWOS:000454987100072
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorBayat, Oğuz
dc.institutionauthorUçan, Osman Nuri
dc.institutionauthorAlAzzawi, Abdulbasit
dc.language.isoen
dc.publisherIeeeen_US
dc.relation.ispartof2017 International Conference on Engineering and Technology (Icet)
dc.relation.ispartofseriesInternational Conference on Engineering and Technology
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectMLPNNen_US
dc.subjectPCAen_US
dc.subjectPREWITTen_US
dc.subjectROBERTSen_US
dc.subjectSOBLEen_US
dc.titleFace recognition based on multi features extractors
dc.typeConference Object

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