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Ghalib Ahmed Salman
Middle Technical University
Computer Science & IT Electrical & Electronics Engineering

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Face recognition using selected topographical features Maitham Ali Naji; Ghalib Ahmed Salman; Muthna Jasim Fadhil
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 5: October 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (565.423 KB) | DOI: 10.11591/ijece.v10i5.pp4695-4700

Abstract

This paper represents a new features selection method to improve an existed feature type. Topographical (TGH) features provide large set of features by assigning each image pixel to the related feature depending on image gradient and Hessian matrix. Such type of features was handled by a proposed features selection method. A face recognition feature selector (FRFS) method is presented to inspect TGH features. FRFS depends in its main concept on linear discriminant analysis (LDA) technique, which is used in evaluating features efficiency. FRFS studies feature behavior over a dataset of images to determine the level of its performance. At the end, each feature is assigned to its related level of performance with different levels of performance over the whole image. Depending on a chosen threshold, the highest set of features is selected to be classified by SVM classifier
Co-Authors Maitham Ali Naji Muthna Jasim Fadhil