A Comparative Analysis of Human Face Recognition Technique PCA and LDA, KPCA Based on Indian Image Dataset

Many statistical techniques for image recognition have been proposed in recent years, different researchers have given the contradictory results when they compared them, In this paper, we compare the two statistical algorithms for image recognition, PCA (Principal Component Analysis), LDA (Linear Discriminant Analysis), linear subspace selection technique and one non linear subspace selection technique KPCA (Kernel Principal Component Analysis) under same conditions. An Indian image data set is used as training and testing data.