A novel nonlinear discriminant analysis method, Kernelized Decision Boundary Analysis (KDBA), is proposed in our paper, whose Decision Boundary feature vectors are the normal vecto...
In this paper, we propose a new algorithm to boost performance of traditional Linear Discriminant Analysis (LDA)-based face recognition (FR) methods in complex FR tasks, where hig...
Juwei Lu, Konstantinos N. Plataniotis, Anastasios ...
Linear Discriminant Analysis (LDA) is widely known feature extraction technique that aims at creating a feature set of enhanced discriminatory power. It was addressed by many resea...
Krzysztof Kucharski, Wladyslaw Skarbek, Miroslaw B...
In this paper, a reformative scatter difference discriminant criterion (SDDC) with fuzzy set theory is studied. The scatter difference between between-class and within-class as di...
The null space of the within-class scatter matrix is found to express most discriminative information for the small sample size problem (SSSP). The null space-based LDA takes full ...