000 04575nam a22004815i 4500
001 978-1-84996-202-5
003 DE-He213
005 20140220084516.0
007 cr nn 008mamaa
008 100623s2010 xxk| s |||| 0|eng d
020 _a9781849962025
_9978-1-84996-202-5
024 7 _a10.1007/978-1-84996-202-5
_2doi
050 4 _aQH323.5
072 7 _aUYQP
_2bicssc
072 7 _aUYQV
_2bicssc
072 7 _aCOM016000
_2bisacsh
082 0 4 _a570.15195
_223
100 1 _aSchuckers, Michael E.
_eauthor.
245 1 0 _aComputational Methods in Biometric Authentication
_h[electronic resource] :
_bStatistical Methods for Performance Evaluation /
_cby Michael E. Schuckers.
264 1 _aLondon :
_bSpringer London :
_bImprint: Springer,
_c2010.
300 _aXXV, 317p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aInformation Science and Statistics,
_x1613-9011
505 0 _aStatistical Background -- Primary Matching and Classification Measures -- False Non-Match Rate -- False Match Rate -- Receiver Operating Characteristic Curve and Equal Error Rate -- Biometric Specific Measures -- Failure to Enrol -- Failure to Acquire -- Additional Topics and Appendices -- Additional Topics and Discussion -- Tables.
520 _aBiometrics, 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.
650 0 _aComputer science.
650 0 _aBiometrics.
650 0 _aComputer science
_xMathematics.
650 1 4 _aComputer Science.
650 2 4 _aBiometrics.
650 2 4 _aMath Applications in Computer Science.
650 2 4 _aComputational Mathematics and Numerical Analysis.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9781849962018
830 0 _aInformation Science and Statistics,
_x1613-9011
856 4 0 _uhttp://dx.doi.org/10.1007/978-1-84996-202-5
912 _aZDB-2-SCS
999 _c110985
_d110985