PERFORMANCE ENHANCEMENT OF FACE RECOGNITION SYSTEM USING PRINCIPAL COMPONENT ANALYSIS MERGED WITH DISCRETE WAVELET TRANSFORMS
Sikandar Afridi, Muhammad Irfan Khattak, Naseem Ullah, Gulzar Ahmad, Muhammad Shafi · 2015
Performance of face recognition system can be enhanced by proposed technique titled as PCA merged with Discrete Wavelet Transform (DWT) instead of using the conventional PCA technique. In this technique to reduce the computational complexity of traditional PCA the size of the image is first reduced by taking the DWT of it. After applying the DWT the facial features of the image are extracted by calculating the Eigenface of the image with size already reduced by taking DWT. As a result of this process the size of database will reduce to one-fourth of the conventional PCA in which the facial features are extracted directly from the image by calculating the Eigenface. The size of the train database is reduced with the proposed technique which reduces the processing time of the face recognition without losing the accuracy. Performance of face recognition system is enhanced in terms of low processing time as shown by comparing the experimental results of conventional PCA and the proposed technique in this paper