Fuzzy kernel discriminant analysis (FKDA) and its application to face recognition
A fuzzy kernel diccriminant analysis algorithm (FKDA) is proposed in this paper, which is the kernel version of the fuzzy fisherface method. First, KPCA is performed on the training data. Then fuzzy k-nearest neighbor (FKNN) is introduced to find the mean vectors of each class. Fuzzy scatter matrices are derived for fuzzy LDA in the kernel space. The results of experiments conducted on ORL database show that the proposed method is better than fuzzy fisherface method in terms of accurate recognition rate.