Face Recognition Based on Nonlinear DCT Discriminant Feature Extraction Using Improved Kernel DCV
Sheng Li, Yongfang Yao, Xiao‐Yuan Jing, Heng Chang, Shi-Qiang Gao, David D. Zhang, Jing-yu YANG · IEICE Transactions on Information and Systems · 2009
This letter proposes a nonlinear DCT discriminant feature extraction approach for face recognition. The proposed approach first selects appropriate DCT frequency bands according to their levels of nonlinear discrimination. Then, this approach extracts nonlinear discriminant features from the selected DCT bands by presenting a new kernel discriminant method, i.e. the improved kernel discriminative common vector (KDCV) method. Experiments on the public FERET database show that this new approach is more effective than several related methods.