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Supporting Decision-making for Biometric System Deployment through Visual Analysis

Turkay, C., Mason, S., Gashi, I. & Cukic, B. (2014). Supporting Decision-making for Biometric System Deployment through Visual Analysis. Paper presented at the Reliability and Security Data Analysis (RSDA) Workshop, International Symposium on Software Reliability Engineering, 03-11-2014-06-11-2014, Naples, Italy.

Abstract

Deployment of biometric systems in the specific environment is not straightforward. Based on pre-deployment performance test results, a decision maker needs to consider the selection of sensors and matching algorithms in terms of the cost, expected false-match and false-non-match failure rates and the underlying quality factors. which depend on operational scenarios, personnel training, demographics, etc. In this paper, we investigate information aggregation through visualization of fingerprint authentication experiments obtained from a large scale data collection with 494 participants. The data was collected using four biometric image capture devices. Each fingerprint image was analysed with two image quality algorithms, and the matching scores were generated using three different matchers. Additionally we collected and analyzed the impact of demographic characteristics, such as gender, age, ethnicity, height and weight, on system performance.

Publication Type: Conference or Workshop Item (Paper)
Additional Information: © 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Publisher Keywords: Security data analysis, Visual analytics, Biometrics, Decision support
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
R Medicine > RA Public aspects of medicine
Departments: School of Science & Technology > Computer Science
School of Science & Technology > Computer Science > giCentre
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