JSIP  Vol.3 No.2 , May 2012
Face Recognition Feature Comparison Based SVD and FFT
Abstract: SVD and FFT are both the efficient tools for image analysis and face recognition. In this paper, we first study the role of SVD and FFT in both filed. Then the decomposition information from SVD and FFT are compared. Next, a new viewpoint that the singular value matrix contains the illumination information of the image is proposed and testified by the experiments based on the ORL face database finally.
Cite this paper: L. Zhao, W. Hu and L. Cui, "Face Recognition Feature Comparison Based SVD and FFT," Journal of Signal and Information Processing, Vol. 3 No. 2, 2012, pp. 259-262. doi: 10.4236/jsip.2012.32035.

[1]   F. Tang, J. Wang and Y. W. Guo, “Facial Feature Detection with Hierarchical Constraints,” Zhejiang University, Hangzhou, 2004.

[2]   S. Lawrence, C. L. Giles and A. C. Tsoi, “Face Recognition: A Convolutional Neural Network Approach,” IEEE Transactions on Neural Networks, Vol. 8, No. 1, 1997, pp. 98-113. doi:10.1109/72.554195

[3]   H. Peng and X. Y. Zhang, “Face Recognition Using DCT—Based Feature Vector,” IEEE International Conference, Vol. 4, 1996, pp. 2144-2147.

[4]   D. L. Swets and J. J. Weng, “Using Discriminant Eigen-features for Image Retrieval,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 18, No. 8, 1996, pp. 831-836.

[5]   P. N. Belhumeur, J. P. Hespanha and D. J. Kriegman, “Eigenfaces vs Fisherfaces: Recognition Using Class Specific Linear Projection,” IEEE Transaction on PAML, Vol. 19, No. 7, 1997, pp. 711-720. doi:10.1109/34.598228

[6]   T. F. Cootes, G. J. Edwards and C. J. Taylor, “Active Appearance Models,” Proceeding of 5th European Conference on Computer Vision, 1998, pp. 484-498.

[7]   X. W. Hou, S. Z. Li, H. J. Zhang and Q. S. Cheng, “Direct Appearance Models,” Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition, Hawaii, December 2001.

[8]   W. Zhao, et al., “Face Recognition: A Literature Survey,” ACM Computing Surveys, Vol. 35. No. 4, 2003, pp. 399-458. doi:10.1145/954339.954342

[9]   Y. X. Lv, Z. Q. Liu and X. H. Zhu, “Image Feature Detection Based on the Principle of Phase Coherency,” Ninth National Youth Communication Conference Proceedings, Electronics Industry Press, Beijing, 2004, pp. 1101-1105.

[10]   J. Zhang, Y. Yan and M. Lades, “Face Recognition: Eigenface, Elastic Matching, and Neural Nets,” Proceedings of the IEEE, Vol. 85, No. 9, 1997, pp. 312-325.

[11]   Z. Hang, “Algebraic Feature Extraction for Recognition,” Pattern Recognition, Vol. 24, No. 3, 1991, pp. 211-219. doi:10.1016/0031-3203(91)90063-B

[12]   S. Romdhani, “Face Recognition Using Principle Components Analysis,” MS Dissertation, University of Glasgow, Glasgow, 1997.

[13]   R. Brunelli and D. Falavigna, “Person Identification Using Multiple Cues,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 17, No. 10, 1995, pp. 968-985. doi:10.1109/34.464560

[14]   M. S. Bartlell, J. R. Movellan and T. J. Se Jnow Ski, “Face Recognition by Independent Component Analysis,” IEEE Transon Neural Networks, Vol. 13, No. 6, 2002, pp. 1450-1464. doi:10.1109/TNN.2002.804287

[15]   G. Du and W. J. Zhu, “Face Recognition Method Based on Singular Value Decomposition and Fuzzy Decision,” Journal of Image and Graphics, Vol. 11, No. 10, 2006, pp. 1456-1459.

[16]   ORL Database.

[17]   G. D. Su, “Questions about the Application of Face Recognition Technology,” China Security, No. 7, 2008, pp. 81-83.