Methodology for the Evaluation of an International Airport Automated Border Control Processing System

MacLeod, Veneta; McLindin, Brett

doi:10.1007/978-3-642-17764-4_4

Cited by 16 publications

(16 citation statements)

References 7 publications

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Section: Evaluation Of the Biometric Recognitionmentioning

confidence: 99%

“…In particular, the operational evaluation of the BVS focuses on aspects such as accuracy of recognition, traveler throughput, and usability, as well as analyzing how these factors influence each other [MacLeod and McLindin 2011]. However, although most aspects can be accurately evaluated in ABC systems, the accuracy evaluation faces some challenges because too few impostor attempts are present [MacLeod and McLindin 2011] and collected biometric data are not readily made public for privacy reasons. In fact, the legislation of some countries does not allow the public dissemination of biometric data (particularly regarding the fingerprint and iris traits), match scores, and decision thresholds obtained and used by the biometric systems installed for government activities [Sprokkereef 2008;Iglezakis 2013].…”

Section: Evaluation Of the Biometric Recognitionmentioning

confidence: 99%

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Biometric Recognition in Automated Border Control

et al. 2016

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The increasing demand for traveler clearance at international border crossing points (BCPs) has motivated research for finding more efficient solutions. Automated border control (ABC) is emerging as a solution to enhance the convenience of travelers, the throughput of BCPs, and national security. This is the first comprehensive survey on the biometric techniques and systems that enable automatic identity verification in ABC. We survey the biometric literature relevant to identity verification and summarize the best practices and biometric techniques applicable to ABC, relying on a real experience collected in the field. Furthermore, we select some of the major biometric issues raised and highlight the open research areas.

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Section: Evaluation Of the Biometric Recognitionmentioning

confidence: 99%

Section: Evaluation Of the Biometric Recognitionmentioning

confidence: 99%

Biometric Recognition in Automated Border Control

et al. 2016

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“…Second, the operational evaluation of the ABC system is more complex than the procedure used in other application scenarios, and the computation of typical figures of merit, such as FAR, FRR or ROC curves is also more difficult. It is therefore necessary to rely on evaluations carried out using public datasets or with internal testing procedures [7]. An alternative is to perform the analysis using a subset of the transactions carried out by the ABC system that guarantees privacy protection [6].…”

Section: Multimodal Biometric Fusion In Abc Systems a Challengesmentioning

confidence: 99%

Enhancing the Performance of Multimodal Automated Border Control Systems

Anand

Labati

Genovese

et al. 2016

2016 International Conference of the Biometrics Special Interest Group (BIOSIG)

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Biometric recognition in Automated Border Control (ABC) systems is performed in response to an increased worldwide traffic, by automatically verifying the identity of the passenger during border crossing. Currently, ABC systems seldom use methods for multimodal biometric fusion, which have been proved to increase the recognition accuracy, due to technological and privacy limitations. This paper proposes a framework for the biometric fusion in ABC systems, with the features of being technology-neutral and privacy-compliant, by performing an analysis of the most suitable biometric fusion techniques for ABC systems and considering the current technical and legal limitations.

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“…The A-machine is a core component of the nowadays eborders concept [7], [9], [11] and mobile systems for large public events such as music festivals, political rallies, or sporting events. In this paper, we consider a particular case of an A-machine which supports an interviewing process as a part of authentication.…”

Section: Introductionmentioning

confidence: 99%

Biometric Intelligence in Authentication Machines: from Talking Faces to Talking Robots

Eastwood

Shmerko

Yanushkevich

et al. 2014

2014 IIAI 3rd International Conference on Advanced Applied Informatics

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Biometric-based intelligence in authentication machines (A-machines) concerns with the problem of balancing human and machine functions in applications such as mass public events and border crossing. The focus of this paper is intelligent human-machine interfacing of behavior biometrics, which seems to play an important role in future generations of A-machines. Various pilot projects use the "talking face" technology. We suggest further improvement to A-machines based on "talking robot" technology: while interviewing the traveler, a humanoid robot recognizes faces and expressions, verifies the e-passports and the traveler (using his/her biometrics), connects with a watchlist (database), generates cognitive questions and analyzes answers, as well as detects soft biometric features in visual and infrared spectrum bands, such as temperature and blood pressure. Various parts of such technology have been implemented, and the feasibility of assembling such a multifunctional system in the form of a robot is to be studied and understood. This paper presents a survey of the related work, and also provides the authors' vision of future generations of A-machines and their applications.

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Methodology for the Evaluation of an International Airport Automated Border Control Processing System

Cited by 16 publications

References 7 publications

Biometric Recognition in Automated Border Control

Biometric Recognition in Automated Border Control

Enhancing the Performance of Multimodal Automated Border Control Systems

Biometric Intelligence in Authentication Machines: from Talking Faces to Talking Robots

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