Face recognition combining the null space approach and the fractional LDA
结合零空间法和F-LDA的人脸识别算法

Linear discriminant analysis is one of the most popular linear projection techniques for feature extraction.The traditional LDA-based methods suffer from two main disadvantages: 1) the small sample size(SSS) problem;2) their optimization criteria are not directly related to the classification accuracy.A new LDA-based technique was proposed,which could overcome the above shortcomings.First, by redefining the within class scatter matrix and the between class scatter matrix,a new null space method was presented.Then,combined the new null space method with F-LDA(fractional LDA) algorithm,a completely new feature extraction algorithm for face recognition was given.The experimental results show that the new LDA-based feature extraction algorithm improves the performance of face recognition significantly.