Statistical Significance as an Aid to System Performance Evaluation

Authors:
Peter Tu;Richard I. Hartley
Affiliations:
-;-
Venue:
ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part II
Year:
2000

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Abstract

Using forensic fingerprint identification as a testbed, a statistical framework for analyzing system performance is presented. Each set of fingerprint features is represented by a collection of binary codes. The matching process is equated to measuring the Hamming distances between feature sets. After performing matching experiments on a small data base, the number of independent degrees of freedom intrinsic to the fingerprint population is estimated. Using this information, a set of independent Bernoulli trials is used to predict the success of the system with respect to a particular dataset.