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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 of the Adaboosting algorithms for the fast detection of regions affected by specular reflection combined with a normalization method based on the local normalization that standardizes the local mean and variance into the located region. A set of measures are proposed to evaluate the effectiveness of detectors. Finally, results are 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.

A Fast Method for Localization of Local Illumination Variations and Photometric Normalization in Face Images