Mobile biometrics represent the new frontier of authentication. The most appealing feature of mobile devices is the wide availability and the presence of more and more reliable sensors for capturing biometric traits, e.g., cameras and accelerometers. Moreover, they more and more often store personal and sensitive data, that need to be protected. Doing this on the same device using biometrics to enforce security seems a natural solution. This makes this research topic attracting and generally promising. However, the growing interest for related applications is counterbalanced by still present limitations, especially for some traits. Acquisition and computation resources are nowadays widely available, but they are not always sufficient to allow a reliable recognition result. Most of all, the way capture is expected to be carried out, i.e., by the user him/herself in uncontrolled conditions and without an expert assistance, can heavily affect the quality of samples and, as a consequence, the accuracy of recognition. Among the biometric traits raising the interest of researchers, iris plays an important role. Mobile Iris CHallenge Evaluation II (MICHE II) competition provided a testbed to assess the progress of mobile iris recognition, as well as its limitations still to overcome. This paper presents the results of the competition and the analysis of achieved performance, that takes into account both proposals submitted for the competition section launched at the 2016 edition of the International Conference on Pattern Recognition (ICPR), as well as proposals submitted for this special issue.

Results from MICHE II – Mobile Iris CHallenge Evaluation II

NAPPI, Michele;
2017

Abstract

Mobile biometrics represent the new frontier of authentication. The most appealing feature of mobile devices is the wide availability and the presence of more and more reliable sensors for capturing biometric traits, e.g., cameras and accelerometers. Moreover, they more and more often store personal and sensitive data, that need to be protected. Doing this on the same device using biometrics to enforce security seems a natural solution. This makes this research topic attracting and generally promising. However, the growing interest for related applications is counterbalanced by still present limitations, especially for some traits. Acquisition and computation resources are nowadays widely available, but they are not always sufficient to allow a reliable recognition result. Most of all, the way capture is expected to be carried out, i.e., by the user him/herself in uncontrolled conditions and without an expert assistance, can heavily affect the quality of samples and, as a consequence, the accuracy of recognition. Among the biometric traits raising the interest of researchers, iris plays an important role. Mobile Iris CHallenge Evaluation II (MICHE II) competition provided a testbed to assess the progress of mobile iris recognition, as well as its limitations still to overcome. This paper presents the results of the competition and the analysis of achieved performance, that takes into account both proposals submitted for the competition section launched at the 2016 edition of the International Conference on Pattern Recognition (ICPR), as well as proposals submitted for this special issue.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11386/4682539
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