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ICDAR 2021 Competition on On-Line Signature Verification
- 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).
- Subjects :
- Biometrics
Computer science
business.industry
Speech recognition
Deep learning
Word error rate
020206 networking & telecommunications
02 engineering and technology
Signature (logic)
Task (project management)
Line (geometry)
0202 electrical engineering, electronic engineering, information engineering
Benchmark (computing)
020201 artificial intelligence & image processing
Artificial intelligence
business
Stylus
Subjects
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