Abstract
Variation in facial image due to illumination plays an important role on the performance of any face recognition system. This type of variation may occur because of the difference in the orientation of the light source and the intensity of illumination. This paper proposes an efficient framework which can handle such type of variations in face recognition process. It uses features from Peri-ocular, nose and mouth regions from the facial image. It has been tested on two publically available databases and has been found that the proposed system could handle the problem of variations in facial images due to variations in illumination in a robust manner.
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References
Heo, J., Savvides, M., Vijayakumar, B.V.K.: Illumination Tolerant Face Recognition Using Phase-Only Support Vector Machines in the Frequency Domain. In: Singh, S., Singh, M., Apte, C., Perner, P. (eds.) ICAPR 2005. LNCS, vol. 3687, pp. 66–73. Springer, Heidelberg (2005)
Karande, K., Talbar, S.: Face Recognition Under Variation of Pose, Illumination Using Independent Component Analysis. International Journal on Graphics, Vision, Image Processing (2008)
Martinez, A., Benavente, R.: The AR Face Database, Technical Report 24, Computer Vision Center (CVC) (June 1998)
Ojala, T., Pietikinen, M., Harwood, D.: A Comparative Study of Texture Measures with Classification Based on Featured Distributions. Pattern Recognition 29(1), 51–59 (1996)
Qing, L., Shan, S., Chen, X., Gao, W.: Face Recognition Under Varying Lighting Based on the Probabilistic Model of Gabor Phase. In: 18th International Conference on Pattern Recognition, ICPR 2006, vol. 3, pp. 1139–1142 (2006)
Tan, X., Triggs, B.: Enhanced local texture feature sets for face recognition under difficult lighting conditions. IEEE Transactions on Image Processing 19(6), 1635–1650 (2010)
Wang, H., Li, S.Z., Wang, Y.: Face Recognition Under Varying Lighting Conditions Using Self Quotient Image. In: 6th IEEE International Conference on Automatic Face and Gesture Recognition, pp. 819–824 (2004)
Xie, X., Lam, K.-M.: An efficient illumination normalization method for face recognition. Pattern Recognition Letters 27(6), 609–617 (2006)
Zou, X., Kittler, J., Messer, K.: Illumination Invariant Face Recognition: A Survey. In: First IEEE International Conference on Biometrics: Theory, Applications, and Systems, BTAS 2007, pp. 1–8 (2007)
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Sharma, A., Kaushik, V.D., Gupta, P. (2014). Illumination Invariant Face Recognition. In: Huang, DS., Bevilacqua, V., Premaratne, P. (eds) Intelligent Computing Theory. ICIC 2014. Lecture Notes in Computer Science, vol 8588. Springer, Cham. https://doi.org/10.1007/978-3-319-09333-8_34
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DOI: https://doi.org/10.1007/978-3-319-09333-8_34
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-09332-1
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