上海交通大学学报(自然版) ›› 2011, Vol. 45 ›› Issue (07): 970-974.

• 自动化技术、计算机技术 • 上一篇    下一篇

基于子空间学习算法的单模态生物特征识别系统

刘欢喜1,吴哲1,朱俊2,李雄1,刘允才1   

  1. (1. 上海交通大学 电子信息与电气工程学院, 上海 200240;2. 江苏骏龙电力科技股份有限公司, 江苏 靖江 214500)
  • 收稿日期:2010-04-11 出版日期:2011-07-29 发布日期:2011-07-29
  • 基金资助:

    国家教委博士点基金资助项目(20110073120028)

Unimodal Biometric System Based on Subspace Learning Method

 LIU  Huan-Xi-1, WU  Zhe-1, ZHU  Jun-2, LI  Xiong-1, LIU  Yun-Cai-1   

  1. (1. School of Electronic, Information and Electrical Engineering, Shanghai Jiaotong University, Shanghai 200240, China;2. Jiangsu Junlong Power Technology Co., Ltd., Jingjiang 214500, Jiangsu, China)
  • Received:2010-04-11 Online:2011-07-29 Published:2011-07-29

摘要: 建立了一种适用于人脸、步态等生物特征识别的单模态生物特征识别系统.首先,单位化原始生物特征数据,得到新的数据集;然后,利用局部拓扑结构保存映射算法,确定新数据集的内蕴低维子空间;最后,在确定的低维子空间上利用类内距离和执行分类.在这个系统中,局部拓扑结构保存映射算法是一种新颖的子空间学习方法,与其他子空间学习算法相比,判别能力更强,更适合于生物特征识别.此外,对原始数据进行单位化处理以及在确定低维子空间上利用类内距离和执行分类都能有效提高生物特征识别系统性能.实验结果表明:该单模态生物特征识别系统是有效性的.

关键词: 单模态生物特征识别系统, 子空间选择, 局部拓扑结构保存映射, 类内距离和

Abstract: This paper built a unimodal biometric system that is suitable for most individual modalities, e.g., face and gait. We first preprocess each raw datum into unit and then obtain a new biometric data set. Then we determine the intrinsic low-dimensional subspace of preprocessed data by local topology structure preserving projections (LTSPP). Finally we perform the classification in the determined subspace using the intra-class distance sum. In the proposed system, LTSPP is a novel subspace algorithm. Compared with other subspace methods, LTSPP possesses more discriminant abilities and is more suitable for biometric recognition. In addition, both preprocessing each raw datum into unit and performing the classification using the intra-class distance sum are helpful to improve the recognition rates. The experimental results demonstrate the effectiveness of our unimodal biometric system.

Key words: unimodal biometric system, subspace selection, local topology structure preserving projections (LTSPP), intraclass distance sum

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