Illumination Compensation of Facial Image Using Combination Algorithm for Face Recognition
Main Article Content
Abstract
So far, biometric identification in general and facial recognition in particular are still being researched and developed for applying in several areas such as security, etc. In this paper, the authors study on some facial image recognition methods that have been researched and published in the world. On the basis of the remaining disadvantages of these published methods, we proposed an illumination compensation method of facial image using Combination Algorithm for face recognition. It is combination method of Singular Value Decomposition and Curvelet algorithm (SVD_C). The results of this proposed method are compared with the results of Global Adaptive Singular Value Decomposition in the Fourier domain method (GASVD_F) and Adaptive Singular Value Decomposition in the Wavelet domain method (ASVD_W) via recognition rate criterion RR (%). Experimental results validate the efficiency of the proposed method.
Keywords
2D discrete wavelet transform, face recognition, illumination compensation, singular value decomposition
Article Details
References
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[6] Jing-Wein Wang, Ngoc Tuyen Le, Jiann-Shu Lee, Chou-Chen Wang, Color face image enhancement using adaptive singular value decomposition in Fourier domain for face recognition. Elsevier, Pattern Recognition, Volume 57, 2016, pp. (31-49).
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[8] Y. Adini, Y. Moses, and S. Ullman, Face recognition: the problem of compensating for changes in illumination direction. IEEE Trans. Pattern Anal., Vol. 19, 1997, pp. (721-732).
[9] W. Chen, M.J. Er, and S. Wu, Illumination compensation and normalization for robust face recognition using discrete cosine transform in logarithm domain. IEEE Trans. Systems, Man, and Cyber., Vol. 36, 2006, pp. (458-466).
[10] H. Demirel and G. Anbarjafari, Pose invariant face recognition using probability distribution functions in different color channels. IEEE Signal Process. Letters, Vol. 15, 2008, pp. (537-540).
[11] J.W. Wang, J.S. Lee, and W.Y. Chen, Face recognition based on projected color space with lighting compensation. IEEE Signal Processing Letters, Vol. 18, 2011, pp. (567-570).
[12] J.W. Wang, Ngoc Tuyen Le, Jiann-Shu Lee, C.C. Wang, Illumination compensation for face recognition using Adaptive Singular Value Decomposition in the Wavelet domain. Elsevier, Information Sciences, Vol. 435 (2018), pp. (69-93).
[13] Satonkar Suhas S., Kurhe Ajay B., Dr. Khanale Prakash B., Face Recognition Using Singular Value Decomposition of Facial Colour Image Database. International Journal of Science and Research (IJSR), ISSN (Online): 2319-7064, Vol. 4, Issue 1, 2015, pp. (249-254).
[14] E. Candes, L. Demanet, David Donoho and Lexing Ying, Fast Discrete Curvelet Transforms. Society for Industrial and Applied Mathematics Journal, Vol. 5, No. 3, 2006, pp. (861-899).
[15] http://www.cs.otago.ac.nz
[2] X. Cao, W. Shen, L.G. Yu, Y.L. Wang, J.Y. Yang, Z.W. Zhang, Illumination invariant extraction for face recognition using neighboring wavelet coefficients.
[3] Haifeng Hu, Variable lighting face recognition using discrete wavelet transform. Elsevier, Pattern Recognition Letters, Vol. 32, 2011, pp. (1526-1534).
[4] Marios Savvides and B.V.K. Vijaya Kumar, Illumination normalization using logarithm transforms for face authentication. AVBPA, Springer, 2003, pp. (549-556).
[5] Shan Du, R. Ward, Wavelet-based illumination normalization for face recognition. IEEE International Conference on Image Processing, 2005. doi:10.1109/ICIP.2005.1530215
[6] Jing-Wein Wang, Ngoc Tuyen Le, Jiann-Shu Lee, Chou-Chen Wang, Color face image enhancement using adaptive singular value decomposition in Fourier domain for face recognition. Elsevier, Pattern Recognition, Volume 57, 2016, pp. (31-49).
[7] H. Han, S. Shan, X. Chen, and W. Gao, A comparative study on illumination preprocessing in face recognition. Pattern Recognition, Vol. 46, 2013, pp. (1691-1699).
[8] Y. Adini, Y. Moses, and S. Ullman, Face recognition: the problem of compensating for changes in illumination direction. IEEE Trans. Pattern Anal., Vol. 19, 1997, pp. (721-732).
[9] W. Chen, M.J. Er, and S. Wu, Illumination compensation and normalization for robust face recognition using discrete cosine transform in logarithm domain. IEEE Trans. Systems, Man, and Cyber., Vol. 36, 2006, pp. (458-466).
[10] H. Demirel and G. Anbarjafari, Pose invariant face recognition using probability distribution functions in different color channels. IEEE Signal Process. Letters, Vol. 15, 2008, pp. (537-540).
[11] J.W. Wang, J.S. Lee, and W.Y. Chen, Face recognition based on projected color space with lighting compensation. IEEE Signal Processing Letters, Vol. 18, 2011, pp. (567-570).
[12] J.W. Wang, Ngoc Tuyen Le, Jiann-Shu Lee, C.C. Wang, Illumination compensation for face recognition using Adaptive Singular Value Decomposition in the Wavelet domain. Elsevier, Information Sciences, Vol. 435 (2018), pp. (69-93).
[13] Satonkar Suhas S., Kurhe Ajay B., Dr. Khanale Prakash B., Face Recognition Using Singular Value Decomposition of Facial Colour Image Database. International Journal of Science and Research (IJSR), ISSN (Online): 2319-7064, Vol. 4, Issue 1, 2015, pp. (249-254).
[14] E. Candes, L. Demanet, David Donoho and Lexing Ying, Fast Discrete Curvelet Transforms. Society for Industrial and Applied Mathematics Journal, Vol. 5, No. 3, 2006, pp. (861-899).
[15] http://www.cs.otago.ac.nz