Real-world biometric applications often operate in the context of an identity transaction that allows up to three attempts. That is, if a biometric sample is acquired and if it does not result in a match, the user is allowed to acquire a second sample, and if it again does not result in a match, the user is allowed to acquire a third sample. If the third sample does not result in a match, then the transaction is ended with no match. We report results of an experiment to determine whether or not successive attempts can be considered as independent samples from the same distribution, and whether and how the quality of a biometric sample changes in successive attempts. To our knowledge, this is the first published research to investigate the statistics of multi-attempt biometric transactions. We find that the common assumption that the attempt outcomes come from independent and identically distributed random variables in multi-attempt biometric transactions is incorrect.
['Adam Czajka', 'Kevin W. Bowyer']
Statistical evaluation of up-to-three-attempt iris recognition