Implementation and evaluation of face recognition based identification system

dc.authorid0000-0001-6444-6659en_US
dc.contributor.authorElbizim, Faruk Can
dc.contributor.authorKasapbaşı, Mustafa Cem
dc.date.accessioned2021-04-13T11:03:30Z
dc.date.available2021-04-13T11:03:30Z
dc.date.issued2017en_US
dc.departmentFakülteler, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümüen_US
dc.description.abstractFace recognition has been widely used and implemented to many systems for the purpose of authentication, identification, finding faces, etc. In this study Yale face database [1] is used which consist of 15 different people. For each of person there are 11 different images with different face expressions. In this study images are categorized as normal, normal and center light, normal and happy, normal with left light and right light. In order to recognize these faces 4 different face recognition methods namely Eigenface, Fisherface, LBPHface and SURF are utilized in the developed environment. In order to test the mentioned face recognition algorithms a software is developed using EmguCV in .NET environment. After evaluating and comparing the obtained confusion matrix amongst other the LBPHface method was found to be superior method with an average accuracy of 99%, it was ~98% SURF, ~97% for EigenFace and FisherFace. FicherFace was slightly better then the Eigenface method.en_US
dc.identifier.endpage63en_US
dc.identifier.startpage60en_US
dc.identifier.urihttps://hdl.handle.net/11467/4840
dc.language.isoenen_US
dc.publisherICATen_US
dc.relation.ispartof5th International Conference on Advanced Technology & Sciences (ICAT'17)en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectFace Recognitionen_US
dc.subjectEigenFacesen_US
dc.subjectFisherFaceen_US
dc.subjectLBPHFaceen_US
dc.subjectSURFen_US
dc.titleImplementation and evaluation of face recognition based identification systemen_US
dc.typeConference Objecten_US

Dosyalar

Orijinal paket
Listeleniyor 1 - 1 / 1
Yükleniyor...
Küçük Resim
İsim:
7.2.3.pdf
Boyut:
857.31 KB
Biçim:
Adobe Portable Document Format
Açıklama:
Lisans paketi
Listeleniyor 1 - 1 / 1
Küçük Resim Yok
İsim:
license.txt
Boyut:
1.56 KB
Biçim:
Item-specific license agreed upon to submission
Açıklama: