Evaluation of face recognition techniques using 2nd order derivative and new feature extraction method based on linear regression slope

Basit Öğe Kaydı
dc.contributor.authorAlazzawi, Abdulbasit
dc.contributor.authorUçan, Osman Nuri
dc.contributor.authorBayat, Oğuz
dc.date.accessioned2021-05-15T12:41:55Z
dc.date.available2021-05-15T12:41:55Z
dc.date.issued2018
dc.departmentMühendislik ve Doğa Bilimleri Fakültesi, Elektrik ve Bilgisayar Mühendisliği Bölümüen_US
dc.description.abstractFace recognition system has been widely utilized for various sensitive applications such as Airport gates, special monitoring, and tracking system. The performance of most face recognition systems would significantly decrease if there were several variations in the illumination of dataset images. In this paper the proposed a new algorithm based on a combination of edge detection operators, features extractors and artificial neural network ANN as a classifier. The Second based on Laplacian comprise Zero cross, Laplacian of gaussian LOG, and Canny edge detection filters. A segmentation process is used to segment each image to equaled size blocks treats face edge pixels precisely. A new features extractor technique based on Linear Regression Slope SLP with discrete wavelet transformation (DWT) and principle components analysis PCA used for features extraction. ANN used for the data set classification and all results obtained evaluated. We tried a combination of various techniques like (Zero cross, DWT, SLP-PCA, ANN),(LOG, DWT, SLP-PCA, ANN),(Canny, DWT, SLP-PCA, ANN). The proposed method is examined and evaluated with different face datasets using ANN classifier. The experimental results were displaying the superiority of the proposed algorithm over the algorithms that used the state-of-art techniques where the combinations (Zero cross, SLP, ANN) gained the best results and could outperform all the other algorithms.en_US
dc.identifier.endpage177en_US
dc.identifier.issn1738-7906
dc.identifier.issue3en_US
dc.identifier.startpage169en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12939/871
dc.identifier.volume18en_US
dc.identifier.wosWOS:000432494400023
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.institutionauthorUçan, Osman Nuri
dc.institutionauthorBayat, Oğuz
dc.institutionauthorAlazzawi, Abdulbasit
dc.language.isoen
dc.publisherInt Journal Computer Science & Network Security-Ijcsnsen_US
dc.relation.ispartofInternational Journal of Computer Science and Network Security
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectFace Recognitionen_US
dc.subjectSLPen_US
dc.subjectPCAen_US
dc.subjectNeural Networken_US
dc.subjectANNen_US
dc.titleEvaluation of face recognition techniques using 2nd order derivative and new feature extraction method based on linear regression slope
dc.typeArticle

Dosyalar

Koleksiyon

WoS İndeksli Yayınlar Koleksiyonu
Bilgisayar Mühendisliği Bölümü Koleksiyonu