This paper presents a novel and interesting combination of wavelet techniques and eigenfaces to extract features for face recognition. Eigenfaces reduce the dimensions of face vectors while wavelets reveal information that is unavailable in the original image. Extensive experiments have been conducted to test the new approach on the ORL face database, using a radial basis function neural network classifier. The results of the experiments are encouraging and the new approach is a step forward in face recognition.