Improvements on the linear discrimination technique with application to face recognition
In this paper, new improvements for the linear discrimination technique are proposed. These improvements include effective solutions for the small sample size problem, the selection of appropriate principal component and more accurate within-class scatter estimation for the Fisher criterion. The effectiveness of our approach is proved by experimental results on the Yale face database.
linear discrimination face recognition small sample size problem within-class scatter estimation principal component selection