A robust face recognition method using multiple features fusion and linear regression

This paper presents a robust face recognition algorithm by using transform domain-based multiple feature fusion and linear regression. Transform domain-based feature fusion can provide comprehensive face information for recognition, and decrease the effect of variations in illumination and pose. The holistic feature and local feature are extracted by discrete cosine transform and Gabor wavelet transform, respectively. Then the extracted holistic features and the local features are fused by weighted sum. The fused feature values are finally sent to linear regression classifier for recognition. The algorithm is evaluated on AR, ORL and Yale B face databases. Experiment results show that our proposed algorithm could be more robust than those single feature-based algorithms under pose and expression variations.