Feature extraction based on fuzzy 2DLDA

In the paper, fuzzy fisherface is extended to image matrix, namely, the fuzzy 2DLDA (F2DLDA). In the proposed method, we calculate the membership degree matrix by fuzzy K-nearest neighbor (FKNN), and then incorporate the membership degree into the definition of the between-class scatter matrix and the within-class scatter matrix. Finally, we get the fuzzy between-class scatter matrix and fuzzy within-class scatter matrix. In our definition of the between-class scatter matrix and within-class matrix, the fuzzy information is better used than fuzzy fisherface. Experiments on the Yale, ORL and FERET face databases show that the new method works well. (C) 2010 Elsevier B.V. All rights reserved.