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
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
An efficient illumination normalization method for face recognition
Pattern Recognition Letters
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CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Face recognition under variable lighting using harmonic image exemplars
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
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ECCV'10 Proceedings of the 11th European conference on Computer vision: Part I
Face recognition using the POEM descriptor
Pattern Recognition
Illumination normalization for face recognition under extreme lighting conditions
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Elliptical local binary patterns for face recognition
ACCV'12 Proceedings of the 11th international conference on Computer Vision - Volume Part I
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Illumination variations that might occur on face images degrade the performance of face recognition systems. In this paper, we propose a novel method of illumination normalization based on retina modeling by combining two adaptive nonlinear functions and a Difference of Gaussians filter. The proposed algorithm is evaluated on the Yale B database and the Feret illumination database using two face recognition methods: PCA based and Local Binary Pattern based (LBP). Experimental results show that the proposed method achieves very high recognition rates even for the most challenging illumination conditions. Our algorithm has also a low computational complexity.