In Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy

Panagiotis Moutafis

will defend his dissertation

Towards Improving Matching in Biometrics Systems

Abstract

The integration of biometric technologies with authentication systems allows us to distinguish individuals easier, faster, and more accurately. As a result, biometric authentication is becoming increasingly important for various applications such as access control and financial transactions. However, despite the encouraging results obtained in controlled environments, biometric authentication remains a challenging problem in real-life conditions. Regardless of whether a biometric system relies on face, fingerprint, or any other biometric trait, it must perform: (i) template matching to generate matching scores that reflect the degree of similarity of the biometric samples matched; and (ii) score-level processing to generate improved similarity scores. Depending on the biometric modality used, different challenges arise that degrade the recognition performance including: (i) distortions due to the different data acquisition conditions; (ii) artifacts introduced by pre-processing algorithms; (iii) incomplete utilization of the available information; and (iv) having to match data from different views.

To address these challenges, we have developed new matching algorithms and score processing methods that increase the recognition performance of biometric systems irrespective of the biometric trait used. Specifically, our contributions include: (i) a method that learns a non-linear distance metric for matching templates from the same view; (ii) a method that maps data from different views to a common discriminant space using non-linear projections; (iii) a score normalization framework that fully utilizes multiple samples per gallery subject, gallery-based information, and past experiences; and (iv) a score normalization framework for multimodal score fusion.

Date: Monday, November 23, 2015
Time: 9:00 AM
Place: HBS 317
Advisor: Prof. Ioannis A. Kakadiaris

Faculty, students, and the general public are invited.