On-Line Signature Matching Based on Hilbert Scanning Patterns

  • Alireza Ahrary
  • Hui-ju Chiang
  • Sei-ichiro Kamata
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5558)


Signature verification is a challenging task, because only a small set of genuine samples can be acquired and usually no forgeries are available in real application. In this paper, we propose a novel approach based on Hilbert scanning patterns and Gaussian mixture models for automatic on-line signature verification. Our system is composed of a similarity measure based on Hilbert scanning patterns and a simplified Gaussian mixture model for decision-level evaluation. To be practical, we introduce specific simplification strategies for model building and training. The system is compared to other state-of-the-art systems based on the results of the First International Signature Verification Competition (SVC 2004). Experiments are conducted to verify the effectiveness of our system.


Hilbert scanning patterns Gaussian mixture model Hilbert scanning distance 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Alireza Ahrary
    • 1
    • 2
  • Hui-ju Chiang
    • 3
  • Sei-ichiro Kamata
    • 4
  1. 1.Fukuoka IndustryScience and Technology FoundationJapan
  2. 2.Information, Production and Systems Research CenterWaseda UniversityJapan
  3. 3.Department of Computer ScienceNational Tsing Hua UniversityTaiwan
  4. 4.Graduate School of Information, Production and SystemsWaseda UniversityJapan

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