Illumination Normalization Using Photometric Linearization
Challenges in face verification research are due the problems of pose, expression and illumination variations. The appearance of a face vary intensely when illumination changes. The purpose of this paper is to present an illumination normalization method for face verification under various lighting conditions. In the proposed approach, a photometric normalization technique called Classified Appearance-based Quotient Image has been applied on the Yale database B and XM2VTS human face databases. The performance of the method under illumination variations is improved compared to other pervious methods. Moreover, the method compensates shadow and specularity components in addition to diffuse reflection.
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Document Type: Research Article
Publication date: December 1, 2013
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