Performance Evaluation of Face Recognition in the Wavelet Domain

In recent years, many different image features have been used for face recognition. The Gabor wavelet feature is the most widely used image feature in face recognition systems because its recognition rate is superior to that of Eigenface systems. However, it remains unclear as to whether Gabor wavelet features are indeed the best wavelet features for face recognition. In this paper, we extract image features of facial images from various wavelet transforms (e.g., Haar, French hat, Mexican hat, Daubechies, Coiflet, Symlet, and O-spline) and evaluate their face recognition performance. We also compare the recognition performance of fixed- and adaptive-scale wavelet features. The results demonstrate that the performance of the wavelets assessed here is similar to that of the Gabor wavelet, and that the performance of adaptive-scale wavelet features is superior to that of fixed-scale features