Abstract
Local Binary Pattern (LBP) is one of the most important facial texture features in face recognition. In this paper, a novel approach based on the LBP is proposed for face recognition under different illumination conditions. The proposed approach applies Difference of Gaussian (DoG) filter in the logarithm domain of face images. LBPs are extracted from the filtered images and used for recognition. A novel measurement is also proposed to calculate distances between different LBPs. The experimental results on the Yale B and Extended Yale B prove superior performances of the proposed method and measurement compared to other existing methods and measurements.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Adini, Y., Moses, Y., Ullman, S.: Face recognition: the problem of compensating for changes in illumination direction. IEEE Transactions on Pattern Analysis and Machine Intelligence 19, 721–732 (1997)
Ahonen, T., Hadid, A., Pietikainen, M.: Face recognition with local binary patterns. In: Proceedings of 8th European Conf. Computer Vision, Prague, Czech Republic, pp. 469–481 (2004)
Ahonen, T., Hadid, A., Pietikainen, M.: Face description with local binary patterns: application to face recognition. IEEE Trans. on Pattern Analysis and Machine Intelligence 28, 2037–2040 (2006)
Jabid, T., Kabir, M.H., Chae, O.: Local Directional Pattern (LDP) for face recognition. In: Proceedings of 2010 Digest of Technical Papers International Conference on Consumer Electronics, Las Vegas, NV, USA, pp. 329–330 (2010)
Tan, X., Triggs, B.: Enhanced local texture feature sets for face recognition under difficult lighting conditions. IEEE Trans. on Image Processing 19, 1635–1650 (2010)
Georghiades, A.S., Belhumeur, P.N., Kriegman, D.J.: From Few to Many: Illumination Cone Models for Face Recognition under Variable Lighting and Pose. IEEE Transactions on Pattern Analysis and Machine Intelligence 23, 643–660 (2001)
Lee, K.C., Ho, J., Kriegman, D.: Acquiring Linear Subspaces for Face Recognition under Variable Lighting. IEEE Transactions on Pattern Analysis and Machine Intelligence 27, 684–698 (2005)
Chen, W., Er, M.J., Wu, S.: Illumination compensation and normalization for robust face recognition using discrete cosine transform in logarithm domain. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics 36, 458–466 (2006)
Xie, X., Lam, K.M.: An efficient illumination normalization method for face recognition. Pattern Recognition Letters 27, 609–617 (2006)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Lian, Z., Er, M.J., Li, J. (2011). A Novel Face Recognition Approach under Illumination Variations Based on Local Binary Pattern. In: Real, P., Diaz-Pernil, D., Molina-Abril, H., Berciano, A., Kropatsch, W. (eds) Computer Analysis of Images and Patterns. CAIP 2011. Lecture Notes in Computer Science, vol 6855. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23678-5_9
Download citation
DOI: https://doi.org/10.1007/978-3-642-23678-5_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-23677-8
Online ISBN: 978-3-642-23678-5
eBook Packages: Computer ScienceComputer Science (R0)