International Joint Conference on Biometrics (IJCB) 2011
The performance of a recognition system is usually experimentally determined.
Therefore, one cannot predict the
performance of a recognition system a priori for a new
dataset. In this paper, a statistical model to predict the
value of k in the rank-k identification rate for a given biometric system is presented.
Thus, one needs to search only
the topmost k match scores to locate the true match object.
A geometrical probability distribution is used to model the
number of non match scores present in the set of similarity scores.
The model is tested in simulation and by us-
ing a public dataset. The model is also indirectly validated
against the previously published results. The actual results
obtained using publicly available database are very close
to the predicted results which validates the proposed model.
