A method for segmentation of local illumination variations and photometric normalization in face images

Abstract

In this paper we present a method for the automatic localization of local light variations and its photometric normalization in face images affected by different angles of illumination causing the appearance of specular light. The proposed approach is faster and more efficient that if the same one was carried out on the whole image through the traditional photometric normalization methods (homomorphic filtering, anisotropic smoothing, etc.). The process consists in using an algorithm for unsupervised image segmentation based on the active contour without edges approach with level set representation model for localization of regions affected by specular reflection combined with a normalization method based on the local normalization that considers the local mean and variance into the located region. The performance of the proposed approach is compared through two experimental schemes to measure how the similarity is affected by illumination changes and how the proposed approach improves the effect caused by these changes. © Springer-Verlag Berlin Heidelberg 2007.