Face Recognition: The Problem of Compensating for Changes in Illumination Direction
IEEE Transactions on Pattern Analysis and Machine Intelligence
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IEEE Transactions on Pattern Analysis and Machine Intelligence
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IEEE Transactions on Pattern Analysis and Machine Intelligence
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SPPRA '07 Proceedings of the Fourth IASTED International Conference on Signal Processing, Pattern Recognition, and Applications
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ICAPR'05 Proceedings of the Third international conference on Pattern Recognition and Image Analysis - Volume Part II
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Although many face recognition techniques have been proposed, recent evaluations in FRVT2006 conclude that relaxing the illumination condition has a dramatic effect on their recognition performance. Among many illumination normalization approaches, histogram matching (HM) is considered one of the most common image-processing-based approaches to cope with illumination. This paper introduces a new illumination normalization approach based on enhancing the image resulting from the HM using the gamma correction and the Retinal filter's compression function; we call it GAMMA-HM-COMP approach. Rather than many other approaches, the proposed one proves its flexibility to different face recognition methods and the suitability for real-life systems in which perfect aligning of the face is not a simple task. The efficiency of the proposed approach is empirically demonstrated using both a PCA-based (Eigenface) and a frequency-based (Spectroface) face recognition methods on both aligned and non-aligned versions of Yale B database. It leads to average increasing in recognition rates ranges from 4 ~ 7 % over HM alone.