Abstract
This paper presents a hybrid fingerprint matching algorithm combining two heterogeneous schemes, namely the texture-vector and minutiae-based methods. The proposed technique has been designed in order to run on a programmable smart card, with image processing and feature extraction performed on the host, and matching performed by the card device. The two matching algorithms have been carefully tuned in order to achieve an acceptable performance despite the computation and memory constraints. Given the high level of intrinsic security that smart cards already have, and the interactive nature of target applications, the complexity of the problem has been greatly reduced, making such an approach feasible. This is validated by the experimental results we show, gathered from an implementation onto a Java Card device, where acceptable false acceptance and rejection rates are achieved at the cost of a reasonable response time of the device.
This work has been partially supported by the European Commission within the IST project 2001-34820 ARTIST, and by the MIUR within the 2002 I4002 PA Project.
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Cucinotta, T., Brigo, R., Di Natale, M. (2004). Hybrid Fingerprint Matching on Programmable Smart Cards. In: Katsikas, S., Lopez, J., Pernul, G. (eds) Trust and Privacy in Digital Business. TrustBus 2004. Lecture Notes in Computer Science, vol 3184. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30079-3_24
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DOI: https://doi.org/10.1007/978-3-540-30079-3_24
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