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Automated border control e-gates and facial recognition systems
José SANCHEZ DEL RIO SAEZ
Daniela Moctezuma
Cristina Conde
Isaac Martín
Enrique Cabello
Acceso Abierto
Atribución-NoComercial-SinDerivadas
https://doi.org/10.1016/j.cose.2016.07.001
Borders
E-gates
Face Recognition
A fast automated biometric solution has been proposed to satisfy the future border control needs of airports resulting from the rapid growth in the number of passengers worldwide. Automated border control (ABC) systems handle the problems caused by this growth, such as congestion at electronic gates (e-gates) or delays in the planned arrival schedules. Different modalities, such as face, fingerprint, or iris recognition, will be used in most of the ABC systems located at airports in the European/Schengen areas. Because facial recognition is the modality that travelers consider most acceptable, it was decided to include this modality in all second generation passports. Face recognition systems, installed in small kiosks inside the e-gates, require high quality facial images to allow high performance and efficiency. Accurate face recognition algorithms, which should be invariant to non-idealities, such as changes in pose and expression, occlusions, and changes in lighting, are also required for these systems. In this paper, a review of the most important face recognition algorithms described in the literature that are invariant to these non-idealities and that can be used in ABC e-gates is presented. A comparative analysis of the most common ABC e-gates located at the different airports is provided. In addition, the results of an experimental evaluation of a face recognition system when halogen, white LEDs, near infra-red, or fluorescence illumination was used, which was conducted in order to determine which type of illumination is optimal for use in ABC e-gates, are presented. To conclude, improvements that could be implemented in the near future in ABC face recognition systems are described.
Elsevier
2016-09
Artículo
Computers & Security Volume 62, September 2016, Pages 49-72
Inglés
Estudiantes
Investigadores
Maestros
INTELIGENCIA ARTIFICIAL
Versión publicada
publishedVersion - Versión publicada
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