Radial correlations in iris patterns, and mutual information within IrisCodes

Abstract

Abstract: 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. We measured the mutual information entailed by radial correlations within each of 632,500 different iris patterns from persons of 152 nationalities. For each iris, we 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. Our measurements of mutual information address how much radial resolution is productive to use when encoding an iris, and we show that a non-uniform allocation of encoding resolution radially leads to significant performance improvements by reducing redundancy.