Bayesian Face Recognition Using Wavelet Transform

A novel hybrid approach based on Bayesian and wavelet transform for face recognition is proposed. Firstly the system uses PCA to select the first 10 candidate images, secondly these candidate images and each testing image are decomposed into low frequency and high frequency sub-band images by applying wavelet transform, Bayesian recognition is parallel processed using these sub-band images. The face recognition result was gained through weigh-adding arraying. Its efficiency and superiority are clarified by comparative experiment on a subset of AR and FERET face data.