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ICDAR 2021 Competition on On-Line Signature Verification

Authors :
Mohamad Wehbi
Juan Carlos Ruiz-Garcia
Ruben Vera-Rodriguez
Marina Bardamova
Moises Diaz
Falk Pulsmeyer
Miguel Ferrer
Santiago Rengifo
Javier Galbally
Mikhail Svetlakov
Sergio Romero-Tapiador
Cintia Lia Szücs
Sumaiya Ahmad
Mohammad Saleem
Ruben Tolosana
Julian Fierrez
Sarthak Mishra
Konstantin Sarin
Jiajia Jiang
Dario Zanca
Yecheng Zhu
Ilya Hodashinsky
Lianwen Jin
Javier Ortega-Garcia
Carlos Gonzalez-Garcia
Songxuan Lai
Marta Gomez-Barrero
Bence Kovari
Aythami Morales
Suraiya Jabin
Artem Slezkin
Source :
Document Analysis and Recognition – ICDAR 2021 ISBN: 9783030863364, ICDAR (4), Sergio Romero Tapiador
Publication Year :
2021
Publisher :
Springer International Publishing, 2021.

Abstract

This paper describes the experimental framework and results of the ICDAR 2021 Competition on On-Line Signature Verification (SVC 2021). The goal of SVC 2021 is to evaluate the limits of on-line signature verification systems on popular scenarios (office/mobile) and writing inputs (stylus/finger) through large-scale public databases. Three different tasks are considered in the competition, simulating realistic scenarios as both random and skilled forgeries are simultaneously considered on each task. The results obtained in SVC 2021 prove the high potential of deep learning methods. In particular, the best on-line signature verification system of SVC 2021 obtained Equal Error Rate (EER) values of 3.33% (Task 1), 7.41% (Task 2), and 6.04% (Task 3).

Details

ISBN :
978-3-030-86336-4
ISBNs :
9783030863364
Database :
OpenAIRE
Journal :
Document Analysis and Recognition – ICDAR 2021 ISBN: 9783030863364, ICDAR (4), Sergio Romero Tapiador
Accession number :
edsair.doi.dedup.....68ca22d354971267768246d69265b60f
Full Text :
https://doi.org/10.1007/978-3-030-86337-1_48