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Multibiometric template generation using CS theory and discrete wavelet transform based fusion technique

机译:使用CS理论和基于离散小波变换的融合技术生成多生物模板

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Nowadays, two or more than two biometric traits or templates are used for individual verification by many institutions due to limitations of the unimodal biometric system. Two or more than two biometric templates are used for recognition by individuals in biometric system which is known as multibiometric system. The problem of generation of multibiometric template is associated with any multibiometric system designing. In this paper, fusion technique for generation of multibiometric template is proposed using compressive sensing theory and Discrete Wavelet Transform. In this technique, sparse measurements of fingerprint image are fused into diagonal wavelet coefficients of face image of the same individual to generate multibiometric template. The fused face image is used for individual recognition for decisions about verification. Defused sparse measurements of fingerprint image from fused face image and then reconstructed fingerprint image using CS recovery processes from extracted sparse measurements. This reconstructed fingerprint image is used for the second level of verification of individuals. This verification accuracy of face system fingerprint system and multibiometric system is above 80 % after application of the proposed fusion algorithm.
机译:如今,由于单峰生物特征识别系统的局限性,许多机构将两个或两个以上的生物特征或模板用于个人验证。两个或两个以上的生物特征模板被用于生物特征系统中的个人识别,该系统被称为多重生物特征系统。多重生物模板的生成问题与任何多重生物系统设计有关。本文利用压缩感知理论和离散小波变换提出了融合多生物模板的技术。在该技术中,将指纹图像的稀疏测量结果融合到同一个人的面部图像的对角小波系数中,以生成多生物模板。融合的面部图像用于个人识别,以决定是否进行验证。从融合的人脸图像中对指纹图像进行解散的稀疏测量,然后使用CS恢复过程从提取的稀疏测量中重建指纹图像。该重建的指纹图像用于个人的第二级验证。应用所提出的融合算法后,人脸系统指纹系统和多重生物系统的验证精度达到80%以上。

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