Face recognition using DWT compression and PSO-based DCT feature selection

摘要

In this paper, a robust face recognition algorithm based on Discrete Wavelet Transform (DWT), Discrete Cosine Transform (DCT) and Particle Swarm Optimization (PSO) is presented. Initially, 2D-DWT is used to compress the data at various levels, which also removes the high frequency noise from the input image. Then DCT is applied to the resulting image to extract coefficients. Finally, the proposed PSO-based feature selection algorithm is utilized to search the feature space for the optimal feature subset where features are carefully selected according to a well defined discrimination criterion. Experimental results compared to the recently proposed algorithms on the ORL face database show that the proposed approach is promising; it is able to select small subsets and still improve the classification accuracy.