Discriminant analysis approach using fuzzy fourfold subspaces model

作者：Song, Xiaoning^*; Yang, Xibei; Yang, Jingyu; Wu, Xiaojun; Zheng, Yujie

来源：Neurocomputing, 2010, 73(10-12): 2255-2265.

DOI：10.1016/j.neucom.2010.01.007

• Fourfold-object model
• Fuzzy discriminant analysis
• Subspace learning
• Feature extraction
• Face recognition

In this paper, some studies have been made on the essence of a novel fuzzy discriminant analysis (FDA) on the fourfold-objective model (FOM). First, a fourfold-objective model on the discriminant analysis is developed, by which a set of integrated subspaces derived from within-class and between-class scatter matrices are constructed, respectively. Second, an improved FDA (IFDA) algorithm based on the relaxed normalized condition is proposed to achieve the distribution information of each sample represented with fuzzy membership grade, which is incorporated into the redefinition of Fisher's scatter matrices. Therefore, the presented algorithm has the potential to outperform the traditional subspace learning algorithms, especially in the cases of small sample size. Experimental results conducted on the ORL, NUST603, FERET and Yale face image databases demonstrate the effectiveness of the proposed method.

• 出版日期2010-6
• 单位江苏科技大学; 江南大学; 中国电子科技集团公司第二十八研究所; 南京理工大学