A survey for handwritten signature verification

Ahmad Sanmorino, Setiadi Yazid

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

23 Citations (Scopus)

Abstract

Signature verification is the process used to recognize an individual's handwritten signature. Signature verification can be divided into two main areas depending on the data acquisition method, off-line and on-line signature verification. In this paper we attempt to survey the signature verification based on three categories. First, judging from how to get the data signature which is off-line and on-line verification. Second, based on the technique used, that is rule-based approach, neural networks, hidden markov model and support vector machine. Third, based on preprocessing and feature extraction, which is thinning and line segmentation. Based on the survey, it was concluded that any method of verification has advantages and disadvantages. However, if viewed from the ease of implementation and performance, using neural networks or hidden markov models are the right choice. Depending on the data acquisition method, on-line verification is recommended to use than off-line verification.

Original languageEnglish
Title of host publicationProceeding of 2012 International Conference on Uncertainty Reasoning and Knowledge Engineering, URKE 2012
Pages54-57
Number of pages4
DOIs
Publication statusPublished - 6 Nov 2012
Event2012 International Conference on Uncertainty Reasoning and Knowledge Engineering, URKE 2012 - Jakarta, Indonesia
Duration: 14 Aug 201215 Aug 2012

Publication series

NameProceeding of 2012 International Conference on Uncertainty Reasoning and Knowledge Engineering, URKE 2012

Conference

Conference2012 International Conference on Uncertainty Reasoning and Knowledge Engineering, URKE 2012
CountryIndonesia
CityJakarta
Period14/08/1215/08/12

Keywords

  • Handwritten Signature
  • Hidden Markov Model
  • Line Segmentation
  • Neural Networks
  • Off-line Verification
  • On-line Verification
  • Rule-Based
  • Support Vector Machine
  • Thinning
  • Verification

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