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A Novel Feature Extraction Descriptor for Face Recognition      
Yazarlar
Ahmed B. Salem Salamh
Doç. Dr. Halil İbrahim AKYÜZ Doç. Dr. Halil İbrahim AKYÜZ
Kastamonu Üniversitesi, Türkiye
Özet
This paper presents a new feature extraction technique for face recognition. The new model, called multi-descriptor, is based on the well-known method of local binary patterns. It involves many different neighborhoods of the central pixel. Its unique advantage is that this descriptor allows the use of different neighborhood sizes instead of only one point. This structure ensures reasonable effectiveness and also provides the possibility to obtain a different distribution of features. Based on the new descriptor, a face recognition model using the pairwise feature descriptor based on the proposed descriptor was developed in this work, and local binary patterns were created to investigate the similarity and dissimilarity between the two models. For both models, the training was done using the support vector machine method on different face databases to overcome face recognition problems such as camera distance, expression, large head size, and illumination variations. The proposed technique achieved perfect accuracy on almost all tested databases including the Extended Yale B and Grimace database.
Anahtar Kelimeler
face recognition | feature extraction | local binary pattern | multi descriptor model
Makale Türü Özgün Makale
Makale Alt Türü ESCI dergilerinde yayımlanan tam makale
Dergi Adı ENGINEERING TECHNOLOGY & APPLIED SCIENCE RESEARCH
Dergi ISSN 2241-4487
Dergi Tarandığı Indeksler ESCI
Makale Dili Türkçe
Basım Tarihi 02-2022
Cilt No 12
Sayı 1
Sayfalar 8033 / 8038
Doi Numarası 10.48084/etasr.4624
Makale Linki http://dx.doi.org/10.48084/etasr.4624
BM Sürdürülebilir Kalkınma Amaçları
Atıf Sayıları
WoS 6
SCOPUS 6
Google Scholar 8
A Novel Feature Extraction Descriptor for Face Recognition

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