Diagonal Maximum Scatter Difference Analysis and its Application to Face Recognition

Abstract:

Diagonal maximum scatter difference (DiaMSD) method for face recognition is proposed in this paper. This novel algorithm is developed based on two techniques, i.e., maximum scatter difference (MSD) and diagonal face images based projection. The DiaMSD method is not only computationally more efficient but also more accurate than the one dimensional (vector-based) MSD method in extracting the facial features for human face recognition. Extensive experiments are performed to test and evaluate the new algorithm using a subset of the FERET face databases. Experimental results show the effectiveness of the proposed method (DiaMSD).

• Periodical: Applied Mechanics and Materials (Volumes 20-23)
• Pages: 123-128
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.20-23.123
• Online since: January 2010
• Authors: Jian Guo Wang, Tie Jun Zhang
• Keywords: Diagonal Face Image, Diagonal MSD (DiaMSD), Face Recognition, Feature Extraction, Maximum Scatter Difference Analysis (MSD)

References

[1] W. Zhao, R. Chellappa, P.J. Phillips and A. Rosenfeld, Face recognition: A literature survey, ACM Comput. Surv, Vol. 35, 399-458 (2003).

DOI: 10.1145/954339.954342

[2] M. Li, B. Yuan, 2D2LDA: a statistical linear discriminant analysis for image matrix, Pattern Recognition Letters, Vol. 26, 527-532 (2005).

DOI: 10.1016/j.patrec.2004.09.007

[3] M. Turk, A. Pentland, Eigenfaces for recognition, J. Cogn. Neurosci, Vol. 3, 71-86 (1991).

[4] D.L. Swets, J. Weng, Using discriminant eigenfeatures for image retrieval, IEEE Trans. Patt. Anal. Mach. Intell, Vol. 18, 831-836 (1996).

DOI: 10.1109/34.531802

[5] P.N. Belhumeur, J.P. Hespanha and D.J. Kriengman, Eigenfaces versus Fisherfaces: recognition using class specific linear projection, IEEE Trans. PAMI, Vol. 19, 711-720 (1997).

DOI: 10.1109/34.598228

[6] L.F. Chen, H.Y.M. Liao, M.T. Ko, J.C. Lin and G.J. Yu, A new LDA-based face recognition system which can solve the small sample size problem, Pattern Recognition Lett, Vol. 33, 1713-1726 (2000).

DOI: 10.1016/s0031-3203(99)00139-9

[7] J. Yang, D. Zhang, A.F. Frangi and J.Y. Yang, Two-dimensional PCA: a new approach to appearance-based face representation and recognition, IEEE Transactions on Pattern Analysis andMachine Intelligence, Vol. 26, 131-137 (2004).

DOI: 10.1109/tpami.2004.1261097

[8] F.X. Song, K. Cheng, J.Y. Yang, Maximum scatter difference, large margin linear projection and support vector machines, Acta automatica sinica, Vol. 30, 890-896 (2004). (in Chinese).

[9] D.Q. Zhang, Z.H. Zhou, S.C. Chen, Diagonal principal component analysis for face recognition, Pattern Recognition, Vol. 39, 140-142 (2006).

DOI: 10.1016/j.patcog.2005.08.002