Wavelet-based illumination normalization algorithm for face recognition
Fuyan Zhang · 2010
The appearance of a face image is severely affected by illumination conditions that hinder the automatic face recognition process.To recognize faces under varying illuminations,a wavelet-based normalization method is proposed so as to normalize illuminations.An image is decomposed into its low frequency and high frequency components.Then different band coefficients are manipulated separately.Histogram equalization is applied to the approximation (low frequency) coefficients and at the same time accentuate the detail (high frequency) coefficients by multiplying by a scalar so as to enhance edges.A normalized image is obtained from the modified coefficients by inverse wavelet transform.Finally,PCA method is used to recognize normalized image with only one training sample.The experimental results obtained by testing on the AR face database and FERRET face database demonstrate the effectiveness of this method with significant improvement in the face recognition system.