A Framework for Biometric and Interaction Performance Assessment of Automated Border Control Processes

Robertson, Joshua J. and Guest, Richard and Elliott, Stephen J. and OConnor, Kevin (2016) A Framework for Biometric and Interaction Performance Assessment of Automated Border Control Processes. IEEE Transactions on Human-Machine Systems, . pp. 1-11. ISSN 2168-2291. (In press) (doi:https://doi.org/10.1109/THMS.2016.2611822) (Full text available)

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http://doi.org/10.1109/THMS.2016.2611822

Abstract

Automated Border Control (ABC) in airports and land crossings utilize automated technology to verify passenger identity claims. Accuracy, interaction stability, user error, and the need for a harmonized approach to implementation are required. Two models proposed in this paper establish a global path through ABC processes. The first, the generic model, maps separately the enrolment and verification phases of an ABC scenario. This allows a standardization of the process and an exploration of variances and similarities between configurations across implementations. The second, the identity claim process, decomposes the verification phase of the generic model to an enhanced resolution of ABC implementations. Harnessing a human-biometric sensor interaction framework allows the identification and quantification of errors within the system's use, attributing these errors to either system performance or human interaction. Data from a live operational scenario are used to analyze behaviors, which aid in establishing what effect these have on system performance. Utilizing the proposed method will aid already established methods in improving the performance assessment of a system. Through analyzing interactions and possible behavioral scenarios from the live trial, it was observed that 30.96% of interactions included some major user error. Future development using our proposed framework will see technological advances for biometric systems that are able to categorize interaction errors and feedback appropriately.

Item Type: Article
Subjects: T Technology
Divisions: Faculties > Sciences > School of Engineering and Digital Arts
Faculties > Sciences > School of Engineering and Digital Arts > Image and Information Engineering
Depositing User: Tina Thompson
Date Deposited: 04 Nov 2016 15:09 UTC
Last Modified: 07 Nov 2016 10:15 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/58404 (The current URI for this page, for reference purposes)
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