Categorizing global and local features of on-line signature verification using DTW and fuzzy logic

Ghazaleh Taherzadeh, Roozbeh Karimi, Alireza Ghobadi, Payam Vahdani Amoli, Seyedali Mirjalili

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

Abstract

In this paper, we study the online signature verification features to define their personalities and categorize them in different groups. We employed 30 features in four categories, a faster methodology using DTW and Fuzzy logic has been applied to find optimal solution based on the lowest Equal Error Rate (EER). At the end, we compare the result with the different methods proposed by other researchers.

Original languageEnglish
Title of host publicationProceedings of the 2011 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2011
Pages349-353
Number of pages5
Publication statusPublished - 1 Dec 2011
Externally publishedYes
Event2011 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2011 - Las Vegas, NV, United States
Duration: 18 Jul 201121 Jul 2011

Publication series

NameProceedings of the 2011 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2011
Volume1

Conference

Conference2011 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2011
CountryUnited States
CityLas Vegas, NV
Period18/07/1121/07/11

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Keywords

  • DTW algorithm
  • EER
  • Features
  • Online signature verification

Cite this

Taherzadeh, G., Karimi, R., Ghobadi, A., Amoli, P. V., & Mirjalili, S. (2011). Categorizing global and local features of on-line signature verification using DTW and fuzzy logic. In Proceedings of the 2011 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2011 (pp. 349-353). (Proceedings of the 2011 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2011; Vol. 1).