Combined face recognition using wavelet packets and radial basis function neural network

In this paper we present a new approach to recognition of frontal faces in color images. It involves face extraction, creation of face models with wavelet packet decomposition for dimensionality reduction, creation of neural classifiers with radial basis functions and combination of classifier results. The first step of the method is face detection through skin-color modeling and segmentation. After the face is extracted, wavelet decomposition is performed. Then, neural classifiers are created respectively for the approximation and details of the wavelet packet decomposition. In the end, combination of classifier results is used to raise overall system availability.