Ear and face based multimodal recognition based on KFDA

Ear recognition is proved to be a promising authentication technique. Because of earpsilas special physiological structure and location, the fusion of ear and face biometrics could fully utilize their connection relationship of physiological location and the supplement between these two biometrics, and possess the advantage of recognizing people without their cooperation. In this paper a novel feature fusion algorithm based on KFDA is proposed and applied to multimodal recognition based on fusion of ear and profile face. With the algorithm, the fusion discriminant vectors of ear and profile face are established and nonlinear feature fusion projection could be implemented. The experimental results show that the method is efficient for feature-level fusion and the ear and face based multimodal recognition performs better than ear or profile face unimodal biometric recognition.