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Face recognition under varying illumination based on Dual-tree complex wavelet transform

As we all know, face recognition usually cares about the main features of a face, such as the shapes and relative positions of the main facial feature, and ignores the illumination changes on the face. Accordingly, A novel method to extract illumination invariant features using the Dual-tree complex wavelet transform for face recognition under varying lighting conditions, the proposed method estimates illumination by minimizing the difference between the normalized illumination and estimated original illumination in the logarithm domain. To evaluate effectiveness of our method, three illumination methods (MSR, SQI and LTV) were implemented using Yale B database. It shows that the performance of the proposed method is better than other methods.