1Department of Information Technology, Sri Subramanya College of Engineering and Technology, Tamilnadu, India.
2Department of Mechanical Engineering, Anna University, Coimbatore, India.
3Department of Mechanical Engineering, Anna University, Coimbatore, India.
*Corresponding author:
A general and efficient design approach using a radial basis function neural classifier to cope with small training sets of high dimension, which is a problem frequently encountered in face recognition, is presented in this paper. In order to minimize the topology of the network used, face features are first extracted and the dimensions are reduced by the principal component analysis method. Then the radial basis function neural network is used as the classifier for face recognition in the second part which uses the feature vector as the input.
Face recognition, principal component analysis, radial basis function neural networks, high dimensional training sets
