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Multi-algorithmic cancelable fingerprint template generation based on weighted sum rule and T-operators

机译:基于加权和规则和T算子的多算法可取消指纹模板生成

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摘要

With the emergence of biometric-based authentication systems in real-world applications, template protection in biometrics is a significant issue to be considered in the recent years. This paper presents two feature set computation algorithms, namely nearest neighbor feature set (NNFS) and Delaunay triangle feature set (DTFS), for a fingerprint sample. Further, the match scores obtained from these algorithms are fused using weighted sum rule and T-operators (T-norms and T-conorms). The experimental evaluation done on FVC 2002 databases confirms the credibility of fusion method compared to each individual algorithm used for fusing. The EER obtained for proposed method is 0 %, 0.059 %, and 3.93 % for FVC 2002 DB1, DB2, and DB3 databases, respectively. This paper also aims to prove the effectiveness of applying T-operators for fusion at score level in fingerprint template protection.
机译:随着基于生物识别的身份验证系统在实际应用中的出现,生物识别中的模板保护已成为近年来需要考虑的重要问题。本文针对指纹样本提出了两种特征集计算算法,即最近邻特征集(NNFS)和Delaunay三角特征集(DTFS)。此外,使用加权和规则和T运算符(T范数和T范数)将从这些算法获得的匹配分数进行融合。与用于融合的每个单独算法相比,在FVC 2002数据库上进行的实验评估证实了融合方法的可靠性。对于FVC 2002 DB1,DB2和DB3数据库,为该方法获得的EER分别为0%,0.059%和3.93%。本文还旨在证明在分数模板保护中应用T运算符进行分数级别融合的有效性。

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