Face Recognition Based Principal Component Analysis And Wavelet Sub bands


Face recognition is important in human identification. The biological recognition technique acts as a good method and broad applications in security areas. This work presents a method to improve the face recognition accuracy using a combination of Principal Component Analysis (PCA), and Wavelet Transform. Wavelet Transform is used to decompose the input image with different levels and rearrangement of subband of wavelet in a way that extract a good information from the image; PCA is used as data redundancy and take the better representation of input data. We apply the proposed method on standard face recognition dataset, the ORL data and dataset from our environment to make the proposed method be practical. The comparison for different levels of wavelet show that the third level has better recognition accuracy with respect to other levels .Finally the performance of the proposed method is compared with other methods and gives better recognition accuracy.