Sciweavers

Share
ICPR
2002
IEEE

Solving the Small Sample Size Problem of LDA

9 years 8 months ago
Solving the Small Sample Size Problem of LDA
The small sample size problem is often encountered in pattern recognition. It results in the singularity of the within-class scatter matrix Sw in Linear Discriminant Analysis (LDA). Different methods have been proposed to solve this problem in face recognition literature. Some methods reduce the dimension of the original sample space and hence unavoidably remove the null space of Sw, which has been demonstrated to contain considerable discriminative information; whereas other methods suffer from the computational problem. In this paper, we propose a new method to make use of the null space of Sw effectively and solve the small sample size problem of LDA. We compare our method with several well-known methods, and demonstrate the efficiency of our method.
Rui Huang, Qingshan Liu, Hanqing Lu, Songde Ma
Added 09 Nov 2009
Updated 09 Nov 2009
Type Conference
Year 2002
Where ICPR
Authors Rui Huang, Qingshan Liu, Hanqing Lu, Songde Ma
Comments (0)
books