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Predicting Fingerprint
Recognition Performance from a Small Gallery
Presented by: Rong Wang
Abstract:
Predicting performance of biometrics is an important problem
in a real world application. In this paper we present a binomial
model to predict fingerprint recognition performance. We use
a fingerprint identification algorithm to find the number
of corresponding triangles as the match and non-match similarity
scores. Then we use these scores in a binomial prediction
model, which uses small gallery to predict performance on
a large population. The results on the entire NIST-4 database
show that our model can reasonably predict large population
performance.
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