A Fast Minutiae-Based Fingerprint Recognition System

H. Xu, Raymond N.J. Veldhuis, Tom A.M. Kevenaar, Ton A.H.M. Akkermans

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    The spectral minutiae representation is a method to represent a minutiae set as a fixed-length feature vector, which is invariant to translation, and in which rotation and scaling become translations, so that they can be easily compensated for. These characteristics enable the combination of fingerprint recognition systems with template protection schemes that require as an input a fixed-length feature vector. Based on the spectral minutiae features, this paper introduces two feature reduction algorithms: the Column Principal Component Analysis and the Line Discrete Fourier Transform feature reductions, which can efficiently compress the template size with a reduction rate of 94%. With reduced features, we can also achieve a fast minutiae-based matching algorithm. This paper presents the performance of the spectral minutiae fingerprint recognition system and shows a matching speed with 125 000 comparisons per second on a PC with Intel Pentium D processor 2.80 GHz and 1 GB of RAM. This fast operation renders our system suitable as a preselector for a large-scale fingerprint identification system, thus significantly reducing the time to perform matching, especially in systems operating at geographical level (e.g., police patrolling) or in complex critical environments (e.g., airports).
    Original languageUndefined
    Article number10.1109/JSYST.2009.2034945
    Pages (from-to)418-427
    Number of pages10
    JournalIEEE systems journal
    Issue number4
    Publication statusPublished - Dec 2009


    • EWI-17389
    • SCS-Safety
    • Fingerprint identification
    • fast minutiae matching
    • Biometrics
    • Template Protection
    • METIS-265782
    • IR-69833
    • feature reduction

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