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Cancelable multi-biometrics: Mixing iris-codes based on adaptive bloom filters

机译:可取消的多重生物测定法:基于自适应布隆过滤器混合虹膜代码

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In this work adaptive Bloom filter-based transforms are applied in order to mix binary iris biometric templates at feature level, where iris-codes are obtained from both eyes of a single subject. The irreversible mixing transform, which generates alignment-free templates, obscures information present in different iris-codes. In addition, the transform is parameterized in order to achieve unlinkability, implementing cancelable multi-biometrics. Experiments which are carried out on the IITD Iris Database version 1.0 confirm the soundness of the proposed approach, (1) maintaining biometric performance at equal error rates below 0.5% for different feature extraction methods and fusion scenarios and (2) achieving a compression of mixed templates down to 10% of original size.
机译:在这项工作中,应用了基于自适应Bloom滤波器的变换,以便在特征级别混合二进制虹膜生物特征模板,其中虹膜代码是从单个对象的两只眼睛获得的。不可逆的混合变换会生成不对齐的模板,从而掩盖了存在于不同虹膜代码中的信息。另外,对变换进行参数化以实现不可链接性,从而实现可取消的多重生物计量。在IITD Iris数据库1.0版上进行的实验证实了该方法的正确性,(1)对于不同的特征提取方法和融合场景,将生物特征性能保持在低于0.5%的相等错误率下,以及(2)实现混合压缩模板缩小到原始大小的10%。

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