On-Line signature matching based on hilbert scanning patterns

Alireza Ahrary*, Hui Ju Chiang, Sei Ichiro Kamata

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationAdvances in Biometrics - Third International Conference, ICB 2009, Proceedings
Pages1190-1199
Number of pages10
DOIs
Publication statusPublished - 2009
Event3rd International Conference on Advances in Biometrics, ICB 2009 - Alghero, Italy
Duration: 2009 Jun 22009 Jun 5

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5558 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference3rd International Conference on Advances in Biometrics, ICB 2009
Country/TerritoryItaly
CityAlghero
Period09/6/209/6/5

Keywords

  • Gaussian mixture model
  • Hilbert scanning distance
  • Hilbert scanning patterns

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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