In this paper, we propose a Wavelet Transform based analysis method for Face Recognition. This algorithm has been used to extract the features of the FERET face database. Results indicate that the proposed methodology is able to achieve excellent performance with only a very small set of features being used, and its error rate is calculated using FAR and FRR. The choice of the Wavelet transform in this setting is motivated by its insensitivity to large variation in light direction, face pose, and facial expression. In the experiments we used Correlation and Threshold values to assure high consistency of the produced classification outcomes. The encouraging experimental results demonstrated that the proposed approach by using frontal and side-view images is a feasible and effective solution to recognizing faces, which can lead to a better and practical use of existing forensic databases in computerized human face-recognition applications.
展开▼
