An improved retina modeling for varying lighting face recognition

Abstract

An improved retina modeling based on bilateral filter is developed for face recognition under variable lighting. Bilateral filter is applied to estimate the adaptation factor X0 (local lighting) in the Naka-Rushton equation, which models nonlinear processing of photoreceptors and outer plexiform layers. Difference of Gaussians filter (DoG) is also used to enhance image contours so as to model inner plexiform layer. Experimental results on the Yale B and CMU PIE face databases indicate the effectiveness of the proposed method. © 2011 Springer-Verlag Berlin Heidelberg.