Multimodal Biometric Recognition Based on Complex KFDA

A novel multimodal biometric recognition algorithm based on complex kernel fisher discriminant analysis (complex KFDA) is proposed. Complex KFDA exploits two phases to generalize KFDA and perform classification for the fusion feature set: complex KPCA plus complex LDA. As two distinct biometric modals, the features of iris and face are fused in parallel to test our algorithm. Experimental results show that the proposed algorithm achieves much better performance than other conventional multimodal biometric algorithms.