Eigenphases for corrupted face images

Abstract

Corrupted face image is one of the important obstacles that machine vision systems encounter when trying to recognize faces. In this paper, we propose a new face recognition system that can deal with the problem of corrupted images more efficiently. The new technique applies the principal component analysis to the phase spectrum of the Fourier transform of the covariance matrix constructed from the MPEG-7 Fourier Feature Descriptor vectors of the images. It will be shown that the proposed technique increases the face recognition rate when applied to images of low resolution and corrupted by noise, compared to other known methods.