Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 30174
A New Approach to Face Recognition Using Dual Dimension Reduction

Authors: M. Almas Anjum, M. Younus Javed, A. Basit

Abstract:

In this paper a new approach to face recognition is presented that achieves double dimension reduction, making the system computationally efficient with better recognition results and out perform common DCT technique of face recognition. In pattern recognition techniques, discriminative information of image increases with increase in resolution to a certain extent, consequently face recognition results change with change in face image resolution and provide optimal results when arriving at a certain resolution level. In the proposed model of face recognition, initially image decimation algorithm is applied on face image for dimension reduction to a certain resolution level which provides best recognition results. Due to increased computational speed and feature extraction potential of Discrete Cosine Transform (DCT), it is applied on face image. A subset of coefficients of DCT from low to mid frequencies that represent the face adequately and provides best recognition results is retained. A tradeoff between decimation factor, number of DCT coefficients retained and recognition rate with minimum computation is obtained. Preprocessing of the image is carried out to increase its robustness against variations in poses and illumination level. This new model has been tested on different databases which include ORL , Yale and EME color database.

Keywords: Biometrics, DCT, Face Recognition, Illumination, Computation, Feature extraction.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1060036

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1304

References:


[1] S Z. Li and J Lu "Face Recognition Using the Nearest Feature Line Method," IEEE transactions on neural networks, vol. 10, no. 2, march 1999.
[2] R. Chellappa, S. Sirohey, C.Wilson, and C. Barnes. "Human and machine recognition of faces: A survey." Technical Report CAR-TR- 731, CS-TR-3339, University of Maryland, August 1994.
[3] P. N. Belhumeur, J.P. Hespanha and D. J. Kriegman, "Eigen-faces vs. Fisherfaces: Recognition Using Class Specific Linear Projection," IEEE Trans. on PAMI,1997.
[4] M. Fleming and G. Cottrell, "Categorization of faces using unsupervised feature extraction," In Proc. IEEE IJCNN International Joint Conference on Neural Networks, 1990.
[5] M. L. Teixeira and J. R. Beveridge, "An Implementation and Study of the Moghaddam and Pentland Intrapersonal/ Extrapersonal Image Difference Face Recognition Algorithm," CSU Computer Science Department Technical Report, May 2003.
[6] B. Moghaddam, W. Wahid and A. Pentland, "Beyond Eigen-faces: Probabilistic Matching for Face Recognition," The 3rd IEEE Int-l Conference on Automatic Face and Gesture Recognition 1998.
[7] X. Xu, "Active Morphable Model for the Analysis and Synthesis of Human Faces," Master Thesis, 2003.
[8] A. Lanitis, C. Taylor and T.Cootes, "Automatic interpretation and coding of face images using flexing models," IEEE Trans. on PAMI, 1997.
[9] R.Brunelli and T Poggio, "Face Recognition: Features versus templates," IEEE Trans. on PAMI, 1993.
[10] D.J. Beymer, "Face recognition under varying pose," A.I.Memo 1461, Center for Biological and Computational Learning, MIT, Cambridge, MA, 1993.
[11] L. Wiskott, J. Fellous, N. Kruger and C. von der malsburg, "Face recognition by elastic bunch graph matching," IEEE Trans. on PAMI, 1997.
[12] L. Wiskott, J. Fellous, N. Kruger and C. von der malsburg, "Face recognition by elastic bunch graph matching," IEEE Trans. on PAMI, 1997.
[13] R. C. Gonzalez, and R. E. Woods, "Digital Image Processing", Addison- Wesely Publishing Company, 1992.
[14] G .Wyszecki. and S. W. Stiles, "Color Science : Concept and Methods, Quantitative Data and Formulas", New York: Wiley, 1982.
[15] L.RJosemar, J.M.Yeloso.Carvalho, "Interpolation / decimation scheme applied to size normalization of character images" International conference on pattern recognition (ICPR-00) vol 2.
[16] M.A.Anjum, M.Y.Javed, A.A.Nadeem and A.Basit, "Face recognition using Scale invariant algorithm", IASTED International conference on Applied Simulation and Modeling ASM 2004,Greece.
[17] E. Burt, and H. Adelson, "The Laplacian Pyramid as a Compact Image Codes",IEEE trans on communication, 2001.
[18] Z M. Hafed and M. D. Levine, "Face Recognition Using the Discrete Cosine Transform"International Journal of Computer Vision" 43(3), 167-188, 2001 c _ 2001.
[19] Color database obtained at Image processing Lab at College of E&ME (NUST), Rawalpindi, Pakistan, Oct, 2004.