The general two-stage class of policies.

<p>In stage 1, for each resident we choose the number of fingers () to acquire and whether ) or not ( to acquire the irises, based on the BFD and BID scores . We then observe the new similarity scores of the acquired biometrics, where the fingerprint scores are ranked according to the index . We compute the likelihood ratio and accept the resident as genuine if is greater than the upper threshold , reject the resident if is smaller than the lower threshold , and otherwise continue to stage 2, where both irises (if ) and additional fingerprints are acquired. Finally, we compute the likelihood ratio based on the biometrics acquired in stage 2 and then accept or reject the resident using the second-stage threshold .</p

The six classes of policies.

<p>The notation used here is introduced in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0094087#pone-0094087-g001" target="_blank">Fig. 1</a>. Note that when , no one proceeds to the second stage.</p

Delay times for both stages.

<p>The number of fingers acquired in stage is for .</p

Parameter values for the fingerprint model.

<p>The inclusion scenario incorporates the FTA rate of 0.0187.</p

Results for the three benchmark policies and the six policies in <b>Table 1</b> in the exclusion scenario.

<p>FRR vs. verification delay tradeoff curves for FRR equals (<b>a</b>) , (<b>b</b>) , (<b>c</b>) and (<b>d</b>) . The mean number of fingers acquired per resident () and the fraction of residents who have their irises acquired are reported for points, a,b,c,x,y,z along two of the tradeoff curves.</p

Parameter values for the iris model.

<p>The inclusion scenario incorporates the FTA rate of 0.0033.</p