Authors: Ammar Chouchane; Mebarka Belahcene; Salah Bourennane
Addresses: Faculty of Science and Technology, Department of Electrical Engineering, University of Mohamed Khider, Biskra, BP 145 RP, 07000 Biskra, Algeria ' Faculty of Science and Technology, Department of Electrical Engineering, University of Mohamed Khider, Biskra, BP 145 RP, 07000 Biskra, Algeria ' Institut Fresnel, UMR CNRS 7249, Ecole Centrale Marseille, France
Abstract: This paper presents an automatic face recognition system in the presence of illumination, expressions and pose variations based on depth and intensity information. At first, the registration of 3D faces is achieved using iterative closest point (ICP). Nose tip point must be located using Maximum Intensity Method. This point usually has the largest depth value; however there is a problem with some unnecessary data such as: shoulders, hair, neck and parts of clothes; to cope with this issue, we propose the integral projection curves (IPC)-based facial area segmentation to extract the facial area. After that, the combined method principal component analysis (PCA) with enhanced Fisher model (EFM) is used to obtain the feature matrix vectors. Finally, the classification is performed using distance measurement and support vector machine (SVM). The experiments are implemented on two face databases CASIA3D and GavabDB; our results show that the proposed method achieves a high recognition performance.
Keywords: IPC-based facial area segmentation; nose tip; 2D face recognition; 3D face recognition; PCA; principal component analysis; EFM; enhanced Fisher model; SVM; support vector machines; integral projection curves; depth images; intensity images; image segmentation; biometrics.
International Journal of Intelligent Systems Technologies and Applications, 2015 Vol.14 No.1, pp.50 - 69
Available online: 05 Oct 2015 *Full-text access for editors Access for subscribers Purchase this article Comment on this article