By Topic

Estimating Sample Size Requirements for Reliable Personal Authentication Using User-Specific Samples

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
J. Bhatnagar ; Indian Institute of Technology, India ; A. Kumar

The goal of this paper is to determine bounds for estimating minimum sample size requirement for reliable biometric identification. A new approach for the reliable estimation of the minimum sample size is proposed for arbitrary ensemble of subjects. A bound on number of acquisitions/samples per subject is arrived through an iterative procedure that tests sequences for user-specific sequences. The approach proposed in this paper is supported by information theoretic measures. These results are fundamental to the integration of concepts from statistics, complexity and probabilistic (Borel) measure spaces. We evolve a novel concept of information equivalence in comparing random sequences for its information content. Furthermore, the problem of missing or lost/corrupted matching scores is also investigated. The solution for these missing biometric matching scores is based on completeness of certain typical space and these scores can be estimated using proposed iterative algorithm.

Published in:

2006 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'06)

Date of Conference:

17-22 June 2006