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1. MULTISCALE LOGARITHM DIFFERENCE EDGEMAPS FOR FACE
RECOGNITION AGAINST VARYING LIGHTING CONDITIONS
ABSTRACT
Lambertian model is a classical illumination modelconsisting of a surface albedo
component and a light intensity component. Some previous researches assume that the
lightintensity component mainly lies in the large-scale features. They adopt holistic image
decompositions to separate it out, but itis difficult to decide the separating point between large-
scaleand small-scale features. In this paper, we propose to take alogarithm transform, which can
change the multiplication ofsurface albedo and light intensity into an additive model. Then,a
difference (substraction) between two pixels in a neighborhoodcan eliminate most of the light
intensity component. By dividinga neighborhood into sub-regions, edge-maps of multiple scales
canbe obtained. Then, each edge-map is multiplied by a weight thatcan be determined by an
independent training scheme. Finally,all the weighted edge-maps are combined to form a robust
holisticfeature map. Extensive experiments on four benchmark data setsin controlled and
uncontrolled lighting conditions show that theproposed method has promising results, especially
in uncontrolledlighting conditions, even mixed with other complicated variations.