Fusion of global and local information for an on-line signature verification system

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper, an on-line signature verification system exploiting local and global information using two-stage fusion is presented. At the first stage, global information is extracted as 13-dimensional vector and recognized by Majority Classifiers, and then local information is extracted as time functions of various dynamic properties and recognized by BP neural network classifier. By fusing global and local information and introducing an enhanced dynamic time warping algorithm and a normalized feature measure, our method obtained an average EER of 4.02% on public database SVC2004(First Signature Verification Competition 2004) Task2 compared to 6.90% the first place at SVC2004.

Original languageEnglish
Title of host publicationProceedings of the 7th International Conference on Machine Learning and Cybernetics, ICMLC
Pages57-61
Number of pages5
DOIs
StatePublished - 2008
Event7th International Conference on Machine Learning and Cybernetics, ICMLC - Kunming, China
Duration: 12 Jul 200815 Jul 2008

Publication series

NameProceedings of the 7th International Conference on Machine Learning and Cybernetics, ICMLC
Volume1

Conference

Conference7th International Conference on Machine Learning and Cybernetics, ICMLC
Country/TerritoryChina
CityKunming
Period12/07/0815/07/08

Keywords

  • Biometrics
  • DTW algorithm
  • Online signature verification
  • Two stage fusion

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