On-line signature partitioning using a population based algorithm

• Autorzy: Zalasiński Marcin , Łapa Krystian , Cpałka Krzysztof , Przybyszewski Krzysztof , Yen Gary G.

Identyfikatory

DOI

10.2478/jaiscr-2020-0001

• Języki publikacji: EN

Abstrakty

EN

The on-line signature is a biometric attribute which can be used for identity verification. It is a very useful characteristic because it is commonly accepted in societies across the world. However, the verification process using this particular biometric feature is a rather difficult one. Researchers working on identity verification involving the on-line signature might face various problems, including the different discriminative power of signature descriptors, the problem of a large number of descriptors, the problem of descriptor generation, etc. However, population-based algorithms (PBAs) can prove very useful when resolving these problems. Hence, we propose a new method for on-line signature partitioning using a PBA in order to improve the verification process effectiveness. Our method uses the Differential Evolution algorithm with a properly defined evaluation function for creating the most characteristic partitions of the dynamic signature. We present simulation results of the proposed method for the BioSecure DS2 database distributed by the BioSecure Association.

Słowa kluczowe

EN

on-line signature; biometrics; signature partitioning; population-based algorithm

PL

podpis on-line; biometria; partycjonowanie sygnatur; algorytm populacyjny

• Wydawca: University of Social Sciences
• Czasopismo: Journal of Artificial Intelligence and Soft Computing Research
• Rocznik: 2020
• Tom: Vol. 10, No. 1
• Strony: 5--13
• Opis fizyczny: Bibliogr. 25 poz., rys.

Twórcy

autor

Zalasiński Marcin

• Częstochowa University of Technology, Department of Computational Intelligence, Poland

autor

Łapa Krystian

• Częstochowa University of Technology, Department of Computational Intelligence, Poland

autor

Cpałka Krzysztof

• Częstochowa University of Technology, Department of Computational Intelligence, Poland

autor

Przybyszewski Krzysztof

• Information Technology Institute, University of Social Sciences, Łód´z, Poland Clark University, Worcester, MA 01610, USA

autor

Yen Gary G.

• School of Electrical and Computer Engineering, Oklahoma State University, Stillwater, OK 74075 USA

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).