Face Recognition Based on Nonlinear DCT Discriminant Feature Extraction Using Improved Kernel DCV

摘要

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 bards by presenting a new kernel discriminant method, i.e. the improved kerpd discriminative common vector (KDCV) method. Experiments on the public FERET database show that this new approach is more effective than several related methods.