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2017 | OriginalPaper | Buchkapitel

A Method for Genetic Selection of the Most Characteristic Descriptors of the Dynamic Signature

verfasst von : Marcin Zalasiński, Krzysztof Cpałka, Yoichi Hayashi

Erschienen in: Artificial Intelligence and Soft Computing

Verlag: Springer International Publishing

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Abstract

Dynamic signature verification is an important area of biometrics. In this area methods from the field of computational intelligence can be used. In this paper we propose a new method for genetic selection of the most characteristic descriptors of the dynamic signature. The descriptors are global features of the signature and components created within its partitions. Selection of the descriptors is realized individually for each user of the biometric system. Its purpose is to increase the precision of the biometric system by eliminating the descriptors which do not increase efficiency of verification procedure. Number of descriptors (their combination) can be high, so the use of genetic algorithm to reduce their number seems to be justified. Moreover, reduction of descriptors increases interpretability of fuzzy mechanism for evaluation of signatures’ similarity. Proposed method was tested using known dynamic signatures database-MCYT-100.

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Vorheriges Kapitel Stability Evaluation of the Dynamic Signature Partitions Over Time

Nächstes Kapitel A Method for Changes Prediction of the Dynamic Signature Global Features over Time

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Titel: A Method for Genetic Selection of the Most Characteristic Descriptors of the Dynamic Signature
verfasst von: Marcin Zalasiński
Krzysztof Cpałka
Yoichi Hayashi
Verlag: Springer International Publishing
Buch: Artificial Intelligence and Soft Computing
Print ISBN: 978-3-319-59062-2

Electronic ISBN: 978-3-319-59063-9

Copyright-Jahr: 2017
DOI: https://doi.org/10.1007/978-3-319-59063-9_67

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