Face recognition using Complete Fuzzy LDA

In this paper, we propose a novel method for feature extraction and recognition, namely, Complete Fuzzy LDA (CFLDA). CFLDA combines the complete LDA and fuzzy set theory. CFLDA redefines the fuzzy between-class scatter matrix and fuzzy within-class scatter matrix that make fully of the distribution of sample and simultaneously extract the irregular discriminative information and regular discriminative information. Experiments on the Yale and FERET face databases show that CFLDA can work well and surpass Fuzzy Fisherface.

• Type: Conference
• Year: 2008
• Where: ICPR
• Authors: Wankou Yang, Hui Yan, Jianguo Wang, Jingyu Yang
• Keywords: Complete Fuzzy LDA, Computer Vision, Fuzzy Between-class Scatter, Fuzzy Within-class Scatter, ICPR 2008