Multiscale Logarithm Difference Edgemaps for Face Recognition Against Varying Lighting Conditions
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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.
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