Face-Iris Identification Using Feature Level Fusion

摘要：

Feature-level fusion remains a challenging problem for multimodal biometrics. However, existing fusion schemes such as sum rule and weighted sum rule are inefficient in complicated condition. In this paper, we propose an efficient feature-level fusion algorithm for iris and face in series. The algorithm first normalizes the original features of iris and face using z-score model, and then connect the normalized feature vectors in serial rule. The proposed algorithm is tested using CASIA iris database and two face databases (ORL database and Yale database). Experimental results show the effectiveness of the proposed algorithm.

关键词： Feature fusion Multimodal biometrics Vnimodal biometrics

作者: Zhifang Wang Chao Liu Zhong Zhang Qun Ding

作者单位: Key Laboratory of Electronics Engineering,College of Heilongjiang Province School of Electronic Engineering,Heilongjiang University Harbin,China

会议类型: 国际会议

会议名称: 2011 3rd International Conference on Computer and Network Technology(ICCNT 2011)(2011第三届IEEE计算机与网络技术国际会议)

会议地点: 太原

会议语种:英文

页码: 388-391

在线出版日期: 2011-02-26（万方平台首次上网日期，不代表论文的发表时间）