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Enhancement of Security through Fused Multimodal Biometric System

机译:通过融合式多模态生物识别系统增强安全性

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Now a days, Person identity is a major issue for security in many applications for example access control, electronic commerce, banking, communications etc. Multimodal biometric technology is the best technology for identification of person than the conventional password based technique. When two or more biometrics used for identification of person then the system called as Multimodal Biometric system. In this paper, we are going to propose a robust security system for personal identification using multimodal biometric system. Three modalities are used in this system face, fingerprint and palm vein. Feature extraction of each modality is done with different algorithm. Local Binary Pattern (LBP) algorithm is used for face feature extraction. Discrete Wavelet transform (DWT) is used for Palm vein feature extraction. And minutiae algorithm is used for finger print feature extraction. Then feature level fusion is done. The proposed method is carried on self generated database images. Finally the more accurate results are achieved. We can further enhance the security adding some encrypted key after fusion.
机译:如今,在许多应用程序中,例如访问控制,电子商务,银行业务,通信等,人员身份已成为安全性的主要问题。与传统的基于密码的技术相比,多模式生物特征识别技术是识别人员的最佳技术。当使用两个或多个生物特征识别人员时,该系统称为多模式生物特征识别系统。在本文中,我们将提出一种使用多模式生物特征识别系统的健壮的个人识别安全系统。在该系统的脸部,指纹和手掌静脉中使用了三种模式。每个模态的特征提取是通过不同的算法完成的。局部二进制模式(LBP)算法用于面部特征提取。离散小波变换(DWT)用于棕榈静脉特征提取。细节算法用于指纹特征提取。然后完成特征级融合。所提出的方法是在自己生成的数据库图像上进行的。最终获得更准确的结果。我们可以在融合后添加一些加密密钥来进一步增强安全性。

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