In this paper, we propose a method for face recognition by using the two-dimensional discrete wavelet transform (2D-DWT) and a new patch strategy. Based on the average image of all training samples, by using integral projection technique for two top-level's high-frequency sub-bands of 2D-DWT, we propose a non-uniform patch strategy for the top-level's low-frequency sub-band. This patch strategy is more suitable to reflect the structure feature of face image; and it is better for retaining the integrity of local information. By applying the obtained patch strategy to all samples, we obtain patches of training samples and testing samples; and then, give the final decision by using the nearest neighbor classifier and the majority voting. Experiments are run on the AR, FERET, Extended Yale B and LFW face databases. The obtained numerical results show that the new face recognition method outperforms the traditional 2D-DWT method and some state-of-the-art patch based methods. 
Non-uniform patch based face recognition via 2D-DWT