This paper presents an effective algorithm for frontal face verification based on the wavelet decomposition technique and Support Vector Machines (SVMs). The process of the proposed method for face verification of M clients consists of two stages.(1) Training stage: by the wavelet decomposition

extracting the appropriate features from the facial images in the prepared training database of faces

training M SVMs for the M clients by the extracted facial feature vectors. (2) Verification stage: selecting a trained SVM from the M SVMs based on the identity claim (such as a name or a password) of an unknown person and using the trained SVM to classify the facial feature vector extracted from the facial image of the unknown person by the wavelet decomposition

and the classification result will show whether or not the identity claim of the unknown person is valid. The ORL database of faces is selected to test and evaluate the proposed algorithm. The results of the test are encouraging and the SVMs in the proposed algorithm are shown to perform very well in classification capability when compared to the traditional radial-basis function networks applied as classifiers in the algorithm.