Earticle

초록

영어

Unimodal biometric systems have to contend with various inherent limitations, such as restricted degrees of freedom, non-universality, susceptibility to spoofing attacks and unacceptable error rates. Multibiometric systems, which fuse two or more biometrics traits together, are able to effectively overcome most of these problems. In this paper, different face traits are fused considering convenient acquiring of visible face and the intrinsic anti-spoofing of thermal face. Initially, the complex fusion strategies at both pixel level and feature level are proposed, which can provide higher discrimination superiority. The 2D-classification methods, including 2DPCA, 2DLDA, (2D)2PCA, (2D)2LDA and (2D)2FPCA are applied into the complex fusion, which can overcome the small size sample problems. Both identification and verification experiments are conducted on the NVIE visible and thermal face database. Various tests based on this database ascertain the efficacy of the proposed approaches in identification and verification. The better performances are in favor of the proposed approaches, FC_(2D)2LDA and FC_(2D)2FPCA, the training number 6 and 8, and the visible face fusion weight 0.4 and 0.6.

목차

Abstract
 1. Introduction
 2. Proposed Complex Fusion Approaches
  2.1. 2D-based Complex Fusion in Pixel Level
  2.2. 2D-Based Complex Fusion in Feature Level
  2.3. Complex Feature Vector Distance
 3. Performance Evaluation with Multi-Modal Biometrics
  3.1. Database Description
  3.2. Comparison between proposed PC_2DPCA and the other Fusion Approaches
  3.3. Performance Comparisons between Proposed Approaches
  3.4. Remarks
 4. Conclusion
 Acknowledgements
 References

키워드

저자

• Ning Wang [ Harbin Institute of Technology ]
• Qiong Li [ Harbin Institute of Technology ] Corresponding author
• Ahmed A. Abd El-Latif [ Harbin Institute of Technology, Menoufia University ]
• Jialiang Peng [ Harbin Institute of Technology, Heilongjiang University ]
• Xiamu Niu [ Harbin Institute of Technology ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Signal Processing, Image Processing and Pattern Recognition

• 간기

  격월간

• pISSN

  2005-4254

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605