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20140310151116.0 |
| 007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION |
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100623s2010 xxk| s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
9781849962025 |
|
978-1-84996-202-5 |
| 050 #4 - LIBRARY OF CONGRESS CALL NUMBER |
|---|
| Classification number |
QH323.5 |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER |
|---|
| Classification number |
570.15195 |
| Edition number |
23 |
| 264 #1 - |
|---|
| -- |
London : |
| -- |
Springer London : |
| -- |
Imprint: Springer, |
| -- |
2010. |
| 912 ## - |
|---|
| -- |
ZDB-2-SCS |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Schuckers, Michael E. |
| Relator term |
author. |
| 245 10 - IMMEDIATE SOURCE OF ACQUISITION NOTE |
|---|
| Title |
Computational Methods in Biometric Authentication |
| Medium |
[electronic resource] : |
| Remainder of title |
Statistical Methods for Performance Evaluation / |
| Statement of responsibility, etc |
by Michael E. Schuckers. |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
XXV, 317p. |
| Other physical details |
online resource. |
| 440 1# - SERIES STATEMENT/ADDED ENTRY--TITLE |
|---|
| Title |
Information Science and Statistics, |
| International Standard Serial Number |
1613-9011 |
| 505 0# - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
Statistical 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 ## - SUMMARY, ETC. |
|---|
| Summary, etc |
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. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Computer science. |
|
|---|
| Topical term or geographic name as entry element |
Biometrics. |
|
|---|
| Topical term or geographic name as entry element |
Computer science |
| General subdivision |
Mathematics. |
|
|---|
| Topical term or geographic name as entry element |
Computer Science. |
|
|---|
| Topical term or geographic name as entry element |
Biometrics. |
|
|---|
| Topical term or geographic name as entry element |
Math Applications in Computer Science. |
|
|---|
| Topical term or geographic name as entry element |
Computational Mathematics and Numerical Analysis. |
| 710 2# - ADDED ENTRY--CORPORATE NAME |
|---|
| Corporate name or jurisdiction name as entry element |
SpringerLink (Online service) |
| 773 0# - HOST ITEM ENTRY |
|---|
| Title |
Springer eBooks |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY |
|---|
| Display text |
Printed edition: |
| International Standard Book Number |
9781849962018 |
| 856 40 - ELECTRONIC LOCATION AND ACCESS |
|---|
| Uniform Resource Identifier |
http://dx.doi.org/10.1007/978-1-84996-202-5 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
|
| Item type |
E-Book |
