期刊名称：International Journal of Signal Processing, Image Processing and Pattern Recognition
印刷版ISSN：2005-4254
出版年度：2013
卷号：6
期号：3
出版社：SERSC
摘要：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.
