An Intelligent Online Signature Verification System

Bin Li, Dapeng Zhang

Research output: Chapter in book / Conference proceedingChapter in an edited book (as author)Academic researchpeer-review

2 Citations (Scopus)

Abstract

The study of human signatures has a long history, but online signature verification is still an active topic in the field of biometrics. This chapter starts with a detailed survey of recent research progress and commercial products, then proposes a typical online dynamic signature verification system based on time-dependent elastic curve matching. Rather than using special dynamic features such as pen pressure and incline, this system uses the 1D curves of signatures which can be captured using a normal tablet. Static and dynamic features can be well extracted from these two curves about x- and y-coordinates and applied to verification. To improve the performance, we introduce into the system different local weight, personal threshold and auto-update algorithms for reference samples. Finally, we present applications of online signature verification for PDAs and in Internet E-commerce.
Original languageEnglish
Title of host publicationComputer-Aided Intelligent Recognition Techniques and Applications
PublisherJohn Wiley & Sons, Ltd
Pages99-117
Number of pages19
ISBN (Print)0470094141, 9780470094143
DOIs
Publication statusPublished - 20 Dec 2005

Keywords

  • Artificial Neural Networks (ANNs)
  • Data acquisition
  • Dynamic time warping (DTW)
  • False Reject Rate or ERR
  • Hidden Markov models (HMMs)
  • Online signature verification
  • Signature Database
  • Signature verification system
  • Time-dependent elastic curve matching

ASJC Scopus subject areas

  • Engineering(all)

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