1 results listed
This paper concentrates on a face biometric system
to investigate the face biometric and problems related to face
recognition under different illumination variations, pose and
partial occlusion. A face recognition system is developed to
recognize face images based on Principal Components Analysis
(PCA). The implemented scheme applies histogram equalization
and mean-and-variance normalization for image preprocessing
step to reduce the effects of the illumination. In order to improve
the recognition performance, we implement a feature selection
method based on Genetic Algorithm (GA). The implemented
method improves the recognition performance of system by
selecting the optimized sub set of PCA features and removing the
irrelevant data. Several datasets of ORL, FERET and BANCA
databases are used in order to test the robustness of the developed
face recognition system.
International Conference on Advanced Technologies, Computer Engineering and Science
ICATCES
Omid Sharifi
M. Ç. YILDIZ
M. ESKANDARI