PCA (principal component analysis) is the optimal dimension compression technique based on second-order information, in the sense of mean-square error. Features extracted by PCA are statistically uncorrelated to each other. ICA (independent component analysis) extracts features for data using their second-order and higher-order information. In the applications on face image recognition, it is hard to say that PCA is superior to ICA or ICA is superior to PCA. The two kinds of features extracted by PCA and IC...