Face Recognition Based on the Phase Spectrum of Local Normalized Image
Jesús Olivares-Mercado, Kazuhiro Hotta, Haruhisa Takahashi, Hector Manuel Perez-Meana, Gabriel Sanchez-Perez · 2008
This paper proposes a robust faces recognition method based on the phase spectrum features of the local normalized image. The principal components analysis (PCA) and the support vector machine (SVM) are used in the classification stage. We evaluate how the proposed method is robust to illumination, occlusion and expressions using "AR face database", which includes the face images of 109 subjects (60 males and 49 females) under illumination changes, expression changes and partial occlusion. The proposed method provides results with a correct recognition rate more than 95.5%.