利用CS理论和基于离散小波变换的融合技术生成多生物特征模板

Rohit M. Thanki, K. Borisagar
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引用次数: 3

摘要

目前,由于单峰生物识别系统的局限性,许多机构使用两个或两个以上的生物特征或模板进行个体验证。在生物识别系统中,个体使用两个或两个以上的生物识别模板进行识别,称为多生物识别系统。多生物特征模板的生成问题与任何多生物特征系统的设计息息相关。本文提出了一种基于压缩感知理论和离散小波变换的多生物特征模板生成融合技术。该技术将指纹图像的稀疏测量值融合到同一个体人脸图像的对角小波系数中,生成多生物特征模板。融合后的人脸图像用于个体识别,以决定是否验证。从融合后的人脸图像中提取指纹图像的稀疏测量值,然后对提取的稀疏测量值进行CS恢复处理重建指纹图像。这种重建的指纹图像用于个人的第二级验证。应用该融合算法后,人脸系统、指纹系统和多生物识别系统的验证准确率均在80%以上。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multibiometric template generation using CS theory and discrete wavelet transform based fusion technique
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.
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