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All Ms Code Bits are Not Created Equal

机译:所有MS代码位都不是相等的

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Many iris recognition systems use filters to extract information about the texture of an iris image. In the Daugman-style approach, the filter output is mapped to a binary iris code. The normalized Hamming distance between two iris codes is computed and decisions about the identity of a person are based on the computed distance. The normalized Hamming distance weights all bits in an iris code equally. However, this work presents experimental evidence that all the bits in an iris code are not equally useful. Some bits are more consistent than others. An explanation of the cause of this discrepancy is given. Different regions of the iris are compared to evaluate their relative consistency. Finally, this paper investigates the theoretical impact of consistent and inconsistent bits on the false reject rate of an iris recognition system.
机译:许多虹膜识别系统使用过滤器来提取有关虹膜图像纹理的信息。在Daugman式方法中,滤波器输出映射到二进制IRIS代码。计算两个虹膜码之间的归一化汉明距离,并且关于人的身份的决定基于计算距离。标准化的汉明距离同样地重量虹膜代码中的所有位。然而,这项工作提出了实验证据,即虹膜代码中的所有位并不同样有用。有些位比其他位更符合。给出了对这种差异的原因的解释。将虹膜的不同区域进行比较,以评估它们的相对一致性。最后,本文研究了一致和不一致的比特对虹膜识别系统的假拒绝率的理论影响。

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