Author/Authors :
Ngadi, Mohammed Systems Engineering Laboratory - National School of Applied Sciences - Ibn Tofail University, Kenitra, Morocco , Amine, Aouatif Systems Engineering Laboratory - National School of Applied Sciences - Ibn Tofail University, Kenitra, Morocco , Nassih, Bouchra Systems Engineering Laboratory - National School of Applied Sciences - Ibn Tofail University, Kenitra, Morocco , Hachimi, Hanaa Systems Engineering Laboratory - National School of Applied Sciences - Ibn Tofail University, Kenitra, Morocco , El-Attar, Adnane Systems Engineering Laboratory - National School of Applied Sciences - Ibn Tofail University, Kenitra, Morocco
Abstract :
The growing demand in the field of security led to the development of interesting approaches in face classification. These worksare interested since their beginning in extracting the invariant features of the face to build a single model easily identifiable byclassification algorithms. Our goal in this article is to develop more efficient practical methods for face detection. We present anew fast and accurate approach based on local binary patterns (LBP) for the extraction of the features that is combined with thenew classifier Neighboring Support Vector Classifier (NSVC) for classification. The experimental results on different natural imagesshow that the proposed method can get very good results at a very short detection time. The best precision obtained by LBP-NSVCexceeds 99%.
Keywords :
Face Classification , LBP , NSVC , Combination
