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A Graph Matching Based Approach to Fingerprint Classification Using Directional Variance

  • Michel Neuhaus
  • Horst Bunke
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3546)

Abstract

In the present paper we address the fingerprint classification problem with a structural pattern recognition approach. Our main contribution is the definition of modified directional variance in orientation vector fields. The new directional variance allows us to extract regions from fingerprints that are relevant for the classification in the Henry scheme. After processing the regions of interest, the resulting structures are converted into attributed graphs. The classification is finally performed with an efficient graph edit distance algorithm. The performance of the proposed classification method is evaluated on the NIST-4 database of fingerprints.

Keywords

Singular Point Edit Distance Directional Variance Graph Match Edit Operation 
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-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Michel Neuhaus
    • 1
  • Horst Bunke
    • 1
  1. 1.Department of Computer ScienceUniversity of BernBernSwitzerland

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