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Abstract
Dynamic signature is a biometric attribute which is commonly used for identity verification. Artificial intelligence methods, especially population-based algorithms (PBAs), can be very useful in the dynamic signature verification process. They are able to, among others, support selection of the most characteristic descriptors of the signature or perform signature partitioning. In this paper, we focus on creating the most characteristic signature partitions using different PBAs and comparing their effectiveness. The simulations whose results are presented in this paper were performed using the BioSecure DS2 database distributed by the BioSecure Association.
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Authors (4)
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Marcin Zalasiński Dr hab. inż.
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Krzysztof Cpałka prof. dr hab. inż.
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Yoichi Hayashi Professor of Computer Science
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Keywords
Details
- Category:
- Monographic publication
- Type:
- rozdział, artykuł w książce - dziele zbiorowym /podręczniku w języku o zasięgu międzynarodowym
- Language:
- English
- Publication year:
- 2020
- Bibliographic description:
- Zalasiński M., Cpałka K., Niksa-Rynkiewicz T., Hayashi Y.: Signature Partitioning Using Selected Population-Based Algorithms// Artificial Intelligence and Soft Computing/ : , 2020, s.480-488
- DOI:
- Digital Object Identifier (open in new tab) 10.1007/978-3-030-61401-0_44
- Verified by:
- Gdańsk University of Technology
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