Comparison of PCA and ICA in Face Recognition

Over the last ten years, face recognition has become a specialized applications area within the larger field of computer vision. Principal component analysis (PCA) and independent component analysis (ICA) become common method for face recognition. This paper compares Principal component analysis (PCA) to independent component analysis (ICA) in face recognition. In this paper, we used PCA derived from "eigenfaces". ICA derived from a linear representation of nongaussian data. In the paper, it shows the different between PCA and ICA.