Multiscale Logarithm Difference Edgemaps for Face Recognition Against Varying Lighting Conditions

Multiscale Logarithm Difference Edgemaps for Face Recognition Against Varying Lighting Conditions

Abstract— Multiscale Logarithm Difference Edgemaps for Face Recognition Against Varying Lighting Conditions. Lambertian model is a classical illumination model consisting of a surface albedo component and a light intensity component. Some previous researches assume that the light intensity component mainly lies in the large-scale features. They adopt holistic image decompositions to separate it out, but it is difficult to decide the separating point between large-scale and small-scale features. In this paper, we propose to take a logarithm transform, which can change the multiplication of surface albedo and light intensity into an additive model. Then, a difference < Final Year Projects 2016 > between two pixels in a neighborhood can eliminate most of the light intensity component.