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Mobile Information Systems
Volume 5 (2009), Issue 2, Pages 105-124

A Multimodal Technique for an Embedded Fingerprint Recognizer in Mobile Payment Systems

V. Conti,1 C. Militello,1 F. Sorbello,1 and S. Vitabile2

1Dipartimento di Ingegneria Informatica, University of Palermo, Viale delle Scienze, Ed. 6 – 90128 - Palermo, Italy
2Dipartimento di Biotecnologie Mediche e Medicina Legale, University of Palermo, Via del Vespro, 129 – 90127 - Palermo, Italy

Received 29 April 2009; Accepted 29 April 2009

Copyright © 2009 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The development and the diffusion of distributed systems, directly connected to recent communication technologies, move people towards the era of mobile and ubiquitous systems. Distributed systems make merchant-customer relationships closer and more flexible, using reliable e-commerce technologies. These systems and environments need many distributed access points, for the creation and management of secure identities and for the secure recognition of users. Traditionally, these access points can be made possible by a software system with a main central server. This work proposes the study and implementation of a multimodal technique, based on biometric information, for identity management and personal ubiquitous authentication. The multimodal technique uses both fingerprint micro features (minutiae) and fingerprint macro features (singularity points) for robust user authentication. To strengthen the security level of electronic payment systems, an embedded hardware prototype has been also created: acting as self-contained sensors, it performs the entire authentication process on the same device, so that all critical information (e.g. biometric data, account transactions and cryptographic keys), are managed and stored inside the sensor, without any data transmission. The sensor has been prototyped using the Celoxica RC203E board, achieving fast execution time, low working frequency, and good recognition performance.