Open AccessBiometrics statistics: a foreword and introduction to the special issue
Author(s) -
Poh Norman,
Schuckers Michael
Publication year - 2015
Publication title -
iet biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.434
H-Index - 28
ISSN - 2047-4946
DOI - 10.1049/iet-bmt.2015.0100
Subject(s) - biometrics , benchmarking , computer science , menagerie , benchmark (surveying) , data science , field (mathematics) , pace , data mining , artificial intelligence , machine learning , mathematics , geography , archaeology , geodesy , marketing , pure mathematics , business
Biometrics technology increasingly plays a central role in personal, national and global security. In order to measure progress any technology provider, engineer or researcher working on biometrics will need to benchmark achievable system performance. Although there have been a number of challenges, competitions, and other efforts to achieve benchmarking in the past, the development of statistical tools, procedures and techniques for evaluating biometric performance has arguably not followed at the same pace. This special issue has gathered four current research papers addressing biometric benchmarking and performance evaluation, with a particular emphasis on evaluation methodologies and statistical methods that render the performance metrics more generalisable, and more reliable. The questions raised above are independent of any biometric modality. This field is closely tied to statistics, yet deeply motivated by the application of biometrics technologies. This gives rise to a relatively new field, which is about statistics for analysing biometrics, or ‘biometrics statistics’.