Research on data fusion of multiple biometric features

机译：多种生物特征数据融合研究

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Given uncertain status reports or notes come from multi-sensor, identity fusion further makes them integrate information and jointly determine the observed entities. This paper discusses an improved data fusion approach to multi-biometric feature, including face, fingerprint and iris image. The approach is called improved multiple biometric data fusion algorithm, based on the eigen-face and the Gabor wavelet methods, incorporating the advantages of the single algorithm. Now we have built a new fusion system, which has demonstrated the improved performance over single biometric systems.

机译：如果不确定状态报告或注释来自多传感器，则身份融合还可以使它们集成信息并共同确定观察到的实体。本文讨论了一种针对多生物特征的改进的数据融合方法，包括脸部，指纹和虹膜图像。该方法被称为改进的多生物特征数据融合算法，它基于特征面和Gabor小波方法，并结合了单一算法的优点。现在，我们已经建立了一个新的融合系统，该系统已经证明了比单一生物识别系统更高的性能。

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《International Conference on Apperceiving Computing and Intelligence Analysis (ICACIA 2009)》|2009年|112-115|共4页
会议地点 Chengdu(CN);Chengdu(CN)
作者
Lin Liu; Xiao-Feng Gu; Jian-Ping Li; Jie Lin; Jin-Xin Shi; Yuan-Yuan Huang;
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School of Software Engineering, University of Electronic Science and Technology of China, Chengdu, 610054, China;

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Data fusion; Gabor wavelet; identification; multi-biometric feature;

机译：数据融合； Gabor小波；识别；多生物特征;

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5. Feature-level fusion in multimodal biometrics. [D] . Govindarajan, Rohin K. 2004

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Research on data fusion of multiple biometric features

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