Abstract
In this paper, we introduce a novel concept of illumination normalization for robust face recognition under different illumination conditions. The concept is extended from the Self Quotient Image (SQI) by which the 2D Gabor filter is applied instead of weighted Gaussian filter in order to increase more efficiency of the face recognition. Our experimental result, which is conducted on Yale face database B, has shown that our proposed method reached a very high recognition rate even in the case of extreme varying illumination.
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Srisuk, S., Petpon, A. (2008). A Gabor Quotient Image for Face Recognition under Varying Illumination. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2008. Lecture Notes in Computer Science, vol 5359. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89646-3_50
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DOI: https://doi.org/10.1007/978-3-540-89646-3_50
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-89645-6
Online ISBN: 978-3-540-89646-3
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