Robust face recognition by combining projection-based image correction and decomposed eigenface

This work presents a robust face recognition method, which can work even when an insufficient number of images are registered for each person. The method is composed of image correction and image decomposition, both of which are specified in the normalized image space (NIS). The image correction [(F. Sakaue and T. Shakunaga, 2004), (T. Shakunaga and F. Sakaue, 2002)] is realized by iterative projections of an image to an eigenspace in NIS. It works well for natural images having various kinds of noise, including shadows, reflections, and occlusions. We have proposed decomposition of an eigenface into two orthogonal eigenspaces [T. Shakunaga and K. Shigenari, 2001], and have shown that the decomposition is effective for realizing robust face recognition under various lighting conditions. This work shows that the decomposed eigenface method can be refined by projection-based image correction.