Search
Abstract
In the verification of identity, the aim is to increase effectiveness and reduce involvement of verified users. A good compromise between these issues is ensured by dynamic signature verification. The dynamic signature is represented by signals describing the position of the stylus in time. They can be used to determine the velocity or acceleration signal. Values of these signals can be analyzed, interpreted, selected, and compared. In this paper, we propose an approach that: (a) uses an evolutionary algorithm to create signature partitions in the time and velocity domains; (b) selects the most characteristic partitions in terms of matching with reference signatures; and (c) works individually for each user, eliminating the need of using skilled forgeries. The proposed approach was tested using Biosecure DS2 database which is a part of the DeepSignDB, a database with genuine dynamic signatures. Our simulations confirmed the correctness of the adopted assumptions.
Citations
-
5
CrossRef
-
0
Web of Science
-
5
Scopus
Authors (8)
-
Marcin Zalasiński Dr hab. inż.
- Częstochowa University of Technology Department of Intelligent Computer Dystem
-
Łukasz Laskowski
- Polish academy of Sciences, Institute of Nuclear Phisics
-
Krzysztof Cpałka prof. dr hab. inż.
- Częstochowa University of Technology, Department of Inteligent Computer System
-
Aleksander Byrski
- AGH Univesity of Science and Technology,
-
Krzysztof Przybyszewski
- University of Social Sciences, Łódź
-
Paweł Trippner
- University of Social Sciences, Łódź
-
Shi Dong
- Zhoukou Normal University
Cite as
Full text
- Publication version
- Accepted or Published Version
- DOI:
- Digital Object Identifier (open in new tab) 10.2478/jaiscr-2022-0018
- License
-
open in new tab
Keywords
Details
- Category:
- Articles
- Type:
- artykuły w czasopismach
- Published in:
-
Journal of Artificial Intelligence and Soft Computing Research
no. 12,
pages 267 - 279,
ISSN: 2083-2567 - Language:
- English
- Publication year:
- 2022
- Bibliographic description:
- Zalasiński M., Laskowski Ł., Niksa-Rynkiewicz T., Cpałka K., Byrski A., Przybyszewski K., Trippner P., Dong S.: Evolutionary Algorithm for Selecting Dynamic Signatures Partitioning Approach// Journal of Artificial Intelligence and Soft Computing Research -Vol. 12,iss. 4 (2022), s.267-279
- DOI:
- Digital Object Identifier (open in new tab) 10.2478/jaiscr-2022-0018
- Sources of funding:
-
- COST_FREE
- Verified by:
- Gdańsk University of Technology
seen 41 times
Recommended for you
Signature Partitioning Using Selected Population-Based Algorithms
- M. Zalasiński,
- K. Cpałka,
- T. Niksa-Rynkiewicz
- + 1 authors
The dynamic signature verification using population-based vertical partitioning
- M. Zalasiński,
- K. Cpałka,
- T. Niksa-Rynkiewicz