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Computational Methods in Biometric Authentication - Statistical Methods for Performance Evaluation (Paperback, 2010 ed.)
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Computational Methods in Biometric Authentication - Statistical Methods for Performance Evaluation (Paperback, 2010 ed.)
Series: Information Science and Statistics
Expected to ship within 10 - 15 working days
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Biometrics, the science of using physical traits to identify
individuals, is playing an increasing role in our
security-conscious society and across the globe. Biometric
authentication, or bioauthentication, systems are being used to
secure everything from amusement parks to bank accounts to military
installations. Yet developments in this field have not been matched
by an equivalent improvement in the statistical methods for
evaluating these systems. Compensating for this need, this unique
text/reference provides a basic statistical methodology for
practitioners and testers of bioauthentication devices, supplying a
set of rigorous statistical methods for evaluating biometric
authentication systems. This framework of methods can be extended
and generalized for a wide range of applications and tests. This is
the first single resource on statistical methods for estimation and
comparison of the performance of biometric authentication systems.
The book focuses on six common performance metrics: for each
metric, statistical methods are derived for a single system that
incorporates confidence intervals, hypothesis tests, sample size
calculations, power calculations and prediction intervals. These
methods are also extended to allow for the statistical comparison
and evaluation of multiple systems for both independent and paired
data. Topics and features: * Provides a statistical methodology for
the most common biometric performance metrics: failure to enroll
(FTE), failure to acquire (FTA), false non-match rate (FNMR), false
match rate (FMR), and receiver operating characteristic (ROC)
curves * Presents methods for the comparison of two or more
biometric performance metrics * Introduces a new bootstrap
methodology for FMR and ROC curve estimation * Supplies more than
120 examples, using publicly available biometric data where
possible * Discusses the addition of prediction intervals to the
bioauthentication statistical toolset * Describes sample-size and
power calculations for FTE, FTA, FNMR and FMR Researchers, managers
and decisions makers needing to compare biometric systems across a
variety of metrics will find within this reference an invaluable
set of statistical tools. Written for an upper-level undergraduate
or master's level audience with a quantitative background, readers
are also expected to have an understanding of the topics in a
typical undergraduate statistics course. Dr. Michael E. Schuckers
is Associate Professor of Statistics at St. Lawrence University,
Canton, NY, and a member of the Center for Identification
Technology Research.
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