Title :
Face recognition using Complete Fuzzy LDA
Author :
Wankou Yang ; Yan, Hui ; Wang, Jianguo ; Yang, Wankou
Author_Institution :
Sch. of Comput. Sci. & Technol., Nanjing Univ. of Sci. & Technol., Nanjing, China
Abstract :
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.
Keywords :
face recognition; feature extraction; fuzzy set theory; matrix algebra; visual databases; CFLDA; complete fuzzy LDA; discriminative information; face databases; face recognition; feature extraction; feature recognition; fuzzy Fisherface; fuzzy within-class scatter matrix; Data mining; Educational technology; Euclidean distance; Face recognition; Feature extraction; Fuzzy set theory; Linear discriminant analysis; Null space; Principal component analysis; Scattering;
Conference_Titel :
Pattern Recognition, 2008. ICPR 2008. 19th International Conference on
Conference_Location :
Tampa, FL
Print_ISBN :
978-1-4244-2174-9
Electronic_ISBN :
1051-4651
DOI :
10.1109/ICPR.2008.4761262
