Method of multimodal biometric data analysis for optimal efficiency evaluation of recognition algorithms and systems

Authors:
V. V. Lobantsov;I. A. Matveev;A. B. Murynin
Affiliations:
Department of Complex Systems, Computer Center, Russian Academy of Sciences, Moscow, Russia 119333;Department of Complex Systems, Computer Center, Russian Academy of Sciences, Moscow, Russia 119333;Department of Complex Systems, Computer Center, Russian Academy of Sciences, Moscow, Russia 119333
Venue:
Pattern Recognition and Image Analysis
Year:
2011

Citing 2
Cited 1

An Introduction to Evaluating Biometric Systems

Computer
An Introduction to Evaluating Biometric Systems

Computer

Optimization of the texture-geometric image model for estimation of the face parameters

Automation and Remote Control

Quantified Score

Hi-index	0.00

Visualization

Abstract

A primary consideration of this paper is to determine different factors influencing the reliability of performance evaluations of remote person recognition algorithms and systems. The authors suggest a method for determining and computing quantitative quality criteria of multimodal biometric data and consider the possibility of extrapolating test results to various practical applications. The functions of biometric data quality and biometric data artificiality that are introduced as a measure of proximity of the available biometric data to biometric data registered "naturally," i.e., data of unaware and noncollaborative subjects, are under examination in this paper.