Date of Award

Spring 2015

Degree Type

Thesis

Degree Name

Master of Science (MS)

Department

Industrial Technology

First Advisor

Stephen Elliott

Committee Chair

Stephen Elliott

Committee Member 1

Mathias Sutton

Committee Member 2

Kevin O'Connor

Abstract

In this thesis, the question of the stability of a group of individual subjects' irises is examined and answered. This stability is examined in regards to the time scale of the month range. The covariate for this research was time. Images collected during one month of separation between captures were examined. The genuine and impostor scores for these images were calculated and then interpreted using the stability score index. This index produced a quantifiable value for the stability of iris match scores over the months of the examination. ^ Additionally, a new framework for collecting and analyzing time in biometrics was created called the biometric time model. This model, which examines inputs from the smallest of phases (subject interactions with a sensor) to the life of the system or user provides detail of user and system metrics that were before unascertainable. With this model, a better understanding of how system and user data that was collected in different time intervals relates. Finally, a proposed method of the consistent language of reporting time in future research is produced.

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