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Minutiae-Based Fingerprint Matching

  • Raffaele Cappelli
  • Matteo Ferrara
  • Davide Maltoni
Part of the Intelligent Systems Reference Library book series (ISRL, volume 37)

Abstract

At today, thanks to the high discriminability of minutiae and the availability of standard formats, minutia-based fingerprint matching algorithms are the most widely adopted methods in fingerprint recognition systems. Many minutiae matching algorithms employ a local minutiae matching stage followed by a consolidation stage. In the local matching stage, local minutiae descriptors are used, since they are discriminant and robust against typical perturbations (e.g., skin and non-linear distortion, partial overlap, rotation, displacement, noise). Minutiae Cylinder-Code representation (MCC), recently proposed by the authors, obtained remarkable performance with respect to state-of-the-art local minutiae descriptors. In this chapter, the basic principles of minutiae-based techniques and local minutiae descriptors are discussed, then the MCC approach is described in detail. Experimental results on standard benchmarks such as FVC2006 and FVC-onGoing are reported to show the great accuracy and efficiency of MCC.

Keywords

Global Score Local Similarity Minutia Extractor Consolidation Stage False Match Rate 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Berlin Heidelberg 2012

Authors and Affiliations

  • Raffaele Cappelli
    • 1
  • Matteo Ferrara
    • 1
  • Davide Maltoni
    • 1
  1. 1.Department of Electronics, Computer Sciences and SystemsUniversity of BolognaCesena(Italy)

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