Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/114108
Title: SVC-onGoing: Signature verification competition
Authors: Tolosana, Ruben
Vera-Rodriguez, Ruben
Gonzalez-Garcia, Carlos
Fierrez, Julian
Morales, Aythami
Ortega-Garcia, Javier
Carlos Ruiz-Garcia, Juan
Romero-Tapiador, Sergio
Rengifo, Santiago
Caruana, Miguel
Jiang, Jiajia
Lai, Songxuan
Jin, Lianwen
Zhu, Yecheng
Galbally, Javier
Diaz, Moises 
Ferrer Ballester, Miguel Ángel 
Gomez-Barrero, Marta
Hodashinsky, Ilya
Sarin, Konstantin
Slezkin, Artem
Bardamova, Marina
Svetlakov, Mikhail
Saleem, Mohammad
Lia Szcs, Cintia
Kovari, Bence
Pulsmeyer, Falk
Wehbi, Mohamad
Zanca, Dario
Ahmad, Sumaiya
Mishra, Sarthak
Jabin, Suraiya
UNESCO Clasification: 3307 Tecnología electrónica
Keywords: Biometrics
Deepsigndb
Handwriting
Signature Verification
SVC 2021, et al
Issue Date: 2022
Journal: Pattern Recognition 
Abstract: This article presents SVC-onGoing1, an on-going competition for on-line signature verification where researchers can easily benchmark their systems against the state of the art in an open common platform using large-scale public databases, such as DeepSignDB2 and SVC2021_EvalDB3, and standard experimental protocols. SVC-onGoing is based on the ICDAR 2021 Competition on On-Line Signature Verification (SVC 2021), which has been extended to allow participants anytime. The goal of SVC-onGoing 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-onGoing prove the high potential of deep learning methods in comparison with traditional methods. In particular, the best signature verification system has obtained Equal Error Rate (EER) values of 3.33% (Task 1), 7.41% (Task 2), and 6.04% (Task 3). Future studies in the field should be oriented to improve the performance of signature verification systems on the challenging mobile scenarios of SVC-onGoing in which several mobile devices and the finger are used during the signature acquisition.
URI: http://hdl.handle.net/10553/114108
ISSN: 0031-3203
DOI: 10.1016/j.patcog.2022.108609
Source: Pattern Recognition [ISSN 0031-3203], v. 127, 108609, (Julio 2022)
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