Online Signature Verification on MOBISIG Finger-Drawn Signature Corpus
Joint Authors
Antal, Margit
Szabó, László Zsolt
Tordai, Tünde
Source
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-15, 15 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-02-14
Country of Publication
Egypt
No. of Pages
15
Main Subjects
Telecommunications Engineering
Abstract EN
We present MOBISIG, a pseudosignature dataset containing finger-drawn signatures from 83 users captured with a capacitive touchscreen-based mobile device.
The database was captured in three sessions resulting in 45 genuine signatures and 20 skilled forgeries for each user.
The database was evaluated by two state-of-the-art methods: a function-based system using local features and a feature-based system using global features.
Two types of equal error rate computations are performed: one using a global threshold and the other using user-specific thresholds.
The lowest equal error rate was 0.01% against random forgeries and 5.81% against skilled forgeries using user-specific thresholds that were computed a posteriori.
However, these equal error rates were significantly raised to 1.68% (random forgeries case) and 14.31% (skilled forgeries case) using global thresholds.
The same evaluation protocol was performed on the DooDB publicly available dataset.
Besides verification performance evaluations conducted on the two finger-drawn datasets, we evaluated the quality of the samples and the users of the two datasets using basic quality measures.
The results show that finger-drawn signatures can be used by biometric systems with reasonable accuracy.
American Psychological Association (APA)
Antal, Margit& Szabó, László Zsolt& Tordai, Tünde. 2018. Online Signature Verification on MOBISIG Finger-Drawn Signature Corpus. Mobile Information Systems،Vol. 2018, no. 2018, pp.1-15.
https://search.emarefa.net/detail/BIM-1204741
Modern Language Association (MLA)
Antal, Margit…[et al.]. Online Signature Verification on MOBISIG Finger-Drawn Signature Corpus. Mobile Information Systems No. 2018 (2018), pp.1-15.
https://search.emarefa.net/detail/BIM-1204741
American Medical Association (AMA)
Antal, Margit& Szabó, László Zsolt& Tordai, Tünde. Online Signature Verification on MOBISIG Finger-Drawn Signature Corpus. Mobile Information Systems. 2018. Vol. 2018, no. 2018, pp.1-15.
https://search.emarefa.net/detail/BIM-1204741
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1204741