Radial correlations in iris patterns, and mutual information within IrisCodes

Radial correlations in iris patterns, and mutual information within IrisCodes

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The discriminating powers of biometric patterns derive from their entropy, just as the hardness of cryptographic keys derive from their entropy. The larger the number of independent bits, or the more independent they are, the less chance of collision. The authors measured the mutual information entailed by radial correlations within each of 632,500 different iris patterns from persons of 152 nationalities. For each iris, they measured how well the sequence of bits in any ring of the IrisCode predicts the sequence of bits in the other rings. Information density is quite non-uniformly distributed across iris patterns radially. Their measurements of mutual information address how much radial resolution is productive to use when encoding an iris, and they show that a non-uniform allocation of encoding resolution radially leads to significant performance improvements by reducing redundancy.

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