Neural Network Based Face Recognition Using
Rbfn Classifier · 2011
Abstract— Face Biometrics is a science of automatically identifying individuals based on their unique facial features. The paper presents neural network classifier(Radial Basis Function Network) to detect frontal views of faces. The curvelet transform, Linear Discriminant Analysis(LDA) are used to extract features from facial images first, and Radial Basis Function Network(RBFN) is used to classify the facial images based on features. Radial Basis Function Network is used to reduce the number of misclassification caused by not-linearly separable classes. 200 images are taken from ORL database and was tested, where the parameters like recognition rate, acceptance ratio and execution time performance are calculated. Neural network based face recognition is robust and has better performance of recognition rate 98.6% and acceptance ratio 85 %.