Wavelet-face based subspace LDA method to solve small sample size problem in face recognition

International Journal of Wavelets, Multiresolution and Information Processing

Volumn 7, Issue 2, 2009, Pages 199-214

  Chen, Wen Sheng ^a,b   Huang, Jian ^c   Zou, Jin ^a   Fang, Bin ^d  

^a LESHAN NORMAL UNIVERSITY   (China)

^b SHENZHEN UNIVERSITY   (China)

^c SUN YAT SEN UNIVERSITY   (China)

^d CHONGQING UNIVERSITY   (China)

Author keywords

Face recognition; Linear discriminant analysis; Small sample size problem; Wavelet feature extraction

Indexed keywords

CONSTRAINT CONDITIONS; DIMENSIONALITY REDUCTIONS; FACE FEATURE EXTRACTIONS; FEATURE SPACES; FERET DATABASE; LINEAR DISCRIMINANT ANALYSIS; NULL SPACES; PROJECTION MATRICES; SCATTER MATRICES; SMALL SAMPLE SIZE PROBLEM; SMALL SAMPLE SIZES; TRAINING SAMPLES; WAVELET FEATURE EXTRACTION; WITHIN-CLASS SCATTER MATRIXES;

DISCRIMINANT ANALYSIS; FEATURE EXTRACTION; IMAGE RETRIEVAL; MATRIX ALGEBRA; WAVELET TRANSFORMS;

FACE RECOGNITION;

EID: 65449137057     PISSN: 02196913     EISSN: None     Source Type: Journal    
DOI: 10.1142/S0219691309002878     Document Type: Article

References (28)

1. R. Chellappa, C. Wilson and S. Sirohey, Human and machine recognition of faces: A survey, Proc. IEEE. 83(5) (1995) 705-740.
2. W. Zhao, R. Chellappa, A. Rosenfeld and J. Phillips, Face recognition: A literature survey, Technical Report, CFAR-TR00-948, University of Maryland (2000); Revised (2002).
3. P. N. Belhumeur, J. P. Hespanha and D. J. Kriegman, Eigenfaces vs. Fisherfaces: Recognition using class specific linear projection, IEEE Trans. Pattern Anal. Mach. Intell. 19(7) (1997) 711-720.
4. L. Chen, H. Liao, M. Ko, J. Lin and G. Yu, A new LDA-based face recognition system, which can solve the small sample size problem, Pattern Recogn. 33(10) (2000) 1713-1726.
5. H. Yu and J. Yang, A direct-LDA algorithm for high-dimensional data with application to face recognition, Pattern Recogn. 34(10) (2001) 2067-2070.
6. Z. Jin, J. Y. Yang, Z. S. Hu and Z. Lou, Face recognition based on the uncorrelated discriminant transform, Pattern Recogn. 34(7) (2001) 1405-1416.
7. W. Zhao, R. Chellappa and P. J. Phillips, Subspace linear discriminant analysis for face recognition, Technical Report CAR-TR-914, CS-TR-4009, University of Maryland at College Park, USA (1999).
8. G. Baudat and F. Anouar, Generalized discriminant analysis using a kernel approach, Neural Comput. 12(10) (2000) 2385-2404.
9. J. Yang, J. Y. Yang and D. Zhang, What's wrong with Fisher Criterion, Pattern Recogn. 35(11) (2002) 2665-2668.
10. R. Huang, Q. Liu, H. Lu and S. Ma, Solving small sample size problem of LDA, in Proc. 16th Int. Conf. Pattern Recogn. (ICPR'02), Vol. 3 (IEEE Computer Society, 2002), pp. 29-32.
11. J. Lu, K. N. Plataniotis and A. N. Venetsanopoulos, Face recognition using LDA-based algorithms, IEEE Trans. Neural Networks 14 1) (2003) 195-200.
12. D. Q. Dai and P. C. Yuen, Regularized discriminant analysis and its application on face recognition, Pattern Recogn. 36(3) (2003) 845-847.
13. W. S. Chen, P. C. Yuen and J. Huang, A new regularized linear discriminant analysis methods to solve small sample size problems, Int. J. Pattern Recogn. Artificial Intell. 19(7) (2005) 917-936.
14. J. Huang, P. C. Yuen, W. S. Chen and J. H. Lai, Component-based subspace linear discriminant analysis method for recognition of face images with one training sample, Optical Eng. 44(5) (2005) 057002.
15. J. Yang, A. F. Frangi, J. Y. Yang, D. Zhang and Z. Jin, KPCA plus LDA: A complete kernel Fisher discriminant framework for feature extraction and recognition, IEEE Trans. Pattern Anal. Mach. Intell. 27(2) (2005) 230-244.
16. W. S. Chen, P. C. Yuen, J. Huang and D. Q. Dai, Kernel machine-based one-parameter regularized Fisher discriminant method for face recognition, IEEE Trans. Syst. Man Cybern. Part B, Cybern. 35 4) (2005) 659-669.
17. W. Zuo, D. Zhang, J. Yang and K. Q. Wang, BDPCA plus LDA: A novel fast feature extraction technique for face recognition, IEEE Trans Syst. Man Cybern. Part B Cybern. 36(4) (2006) 946-953.
18. H. Y. Wang, Z. F. Wang, Y. L. Xiao, J. Wu and Q. Li, PCA plus F-LDA: A new approach to face recognition, Int. J. Pattern Recogn. Artificial Intell. 21(6) (2007) 1059-1068.
19. M. Kyperountas, A. Tefas and I. Pitas, Weighted piecewise LDA for solving the small sample size problem in face verification, IEEE Trans. Neural Networks 18(2) (2007) 506-519.
20. P. J. Phillips, H. Moon, S. A. Rizvi and P. J. Rauss, The FERET evaluation methodology for face recognition algorithms, IEEE Trans. Pattern Anal. Mach. Intell. 22(10) (2000) 1090-1104.
21. S. Mallat, A theory for multiresolution signal decomposition: The wavelet representation, IEEE Trans. Pattern Anal. Mach. Intell. 11(7) (1989) 674-693.
22. L. Q. Li and Y. Y. Tang, Wavelet-Hough transform with application in edge and target detections, Int. J. Wavelets Multiresolut. Inf. Process 4(3) (2006) 567-587.
23. L. Nanni and A. Lumini, Wavelet decomposition tree selection for palm and face authentication, Pattern Recogn. Lett. 29(3) (2008) 343-353.
24. Y. Meyer, Wavelets and Operators (Cambridge University Press, Cambridge, UK, 1993).
25. B. U. Shankar, S. K. Meher and A. Ghosh, Neuro-wavelet classifier for multispectral remote sensing images, Int. J. Wavelets Multiresolut. Inf. Process. 5(4) (2007) 589-611.
26. J. H. Lai, P. C. Yuen and G. C. Feng, Face recognition using holistic Fourier invariant features, Pattern Recogn. 34(1) (2001) 95-109.
27. B. Fang, X. G. You, W. S. Chen and Y. Y. Tang, Matching algorithm using wavelet thinning features for offline signature verification, Int. J. Wavelets Multiresolut. Inf. Process. 5(1) (2007) 27-38.
28. M. Acharyya and M. K. Kundu, Extraction of noise tolerant, grayscale transform and rotation invariant features for texture segmentation using wavelet frames, Int. J. Wavelets Multiresolut. Inf. Process. 6 3) (2008) 391-417.