Abstract
In this paper, different from most of existing methods, an additive term as noise is considered in the proposed method besides a multiplicative illumination term in the illumination model. Discrete cosine transform coefficients of high frequency band are discarded to eliminate the effect caused by noise. Based on local characteristic of human face, a simple but effective illumination normalization method local relation map is proposed. The experimental results on the Yale B and Extended Yale B prove the outperformance and lower computational burden of the proposed method compared to other existing methods.
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© 2011 Springer-Verlag Berlin Heidelberg
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Lian, Z., Er, M.J., Li, J. (2011). A Novel Local Illumination Normalization Approach for Face Recognition. In: Liu, D., Zhang, H., Polycarpou, M., Alippi, C., He, H. (eds) Advances in Neural Networks – ISNN 2011. ISNN 2011. Lecture Notes in Computer Science, vol 6676. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21090-7_41
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DOI: https://doi.org/10.1007/978-3-642-21090-7_41
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-21089-1
Online ISBN: 978-3-642-21090-7
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