Image understanding for iris biometrics: A survey
Computer Vision and Image Understanding
Robust iris recognition using advanced correlation techniques
ICIAR'05 Proceedings of the Second international conference on Image Analysis and Recognition
IEEE Transactions on Circuits and Systems for Video Technology
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In this paper, we demonstrate how to reduce the chance of a spoofed iris code being falsely accepted by an iris recognition system. We simulate the system attack by taking one of the registered iris codes from a subject set and mutating it by several different rates and presenting the resultant iris codes to our system. Our approach uses the k-nearest neighbors from a training set to the known spoof to establish a critical distance. Presented iris codes from our mutant set that have a Hamming Ratio when compared to the spoof that is less than the critical distance are rejected. Those that are falsely accepted are totaled to produce a Spoof False Accept Rate (SP-FAR). The second phase of our approach uses traditional iris code recognition to reduce the SP-FAR by rejecting those spoofs that were mutated to a degree such that they will not match any of the other iris codes in the training set.