A Novel Feature Extraction Descriptor for Face Recognition
Yazarlar (2)
Ahmed B. Salem Salamh
Kastamonu Üniversitesi
Kastamonu Üniversitesi
Doç. Dr. Halil İbrahim AKYÜZ Kastamonu Üniversitesi, Türkiye
| Makale Türü |
Özgün Makale
(ESCI dergilerinde yayınlanan tam makale)
|
||
| Dergi Adı | ENGINEERING TECHNOLOGY & APPLIED SCIENCE RESEARCH | ||
| Dergi ISSN | 2241-4487 Wos Dergi Scopus Dergi | ||
| Dergi Tarandığı Indeksler | ESCI | ||
| Makale Dili | Türkçe | Basım Tarihi | 02-2022 |
| Kabul Tarihi | – | Yayınlanma Tarihi | 12-02-2022 |
| Cilt / Sayı / Sayfa | 12 / 1 / 8033–8038 | DOI | 10.48084/etasr.4624 |
| Makale Linki | http://dx.doi.org/10.48084/etasr.4624 | ||
| UAK Araştırma Alanları |
Bilişim Teknolojileri Eğitimi
Eğitim Teknolojileri
Öğretim Tasarımı
|
||
| 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 |
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| Web of Science | 6 |
| Google Scholar | 13 |