Fusion of Face and Palmprint for Personal Identification Based on Ordinal Features

Rufeng Chu, Shengcai Liao, Yufei Han, Zhenan Sun, Stan Z. Li, Tieniu Tan

Abstract: In this paper, we present a face and palmprint multimodal biometric identification method and system to improve the identification performance. Effective classifiers based on ordinal features are constructed for faces and palmprints, respectively. Then, the matching scores from the two classifiers are combined using several fusion strategies. Experimental results on a middle-scale data set have demonstrated the effectiveness of the proposed system.