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2017 | OriginalPaper | Buchkapitel

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

verfasst von : Marcin Zalasiński, Krystian Łapa, Krzysztof Cpałka, Takamichi Saito

Erschienen in: Artificial Intelligence and Soft Computing

Verlag: Springer International Publishing

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Abstract

Dynamic signature can be represented by a set of global features. These features are interpreted as e.g. number of pen ups, time of signing process, etc. Values of global features can be determined on the basis of non-linear waveforms defining dynamics of the signature. They are acquired using graphic tablet or a device with a touch screen. In this paper we present a method for prediction values of the dynamic signature global features changing over time. The purpose of the prediction is, among others, improving the efficiency of the dynamic signature verification process when the interval between acquisition sessions is large. This interval causes a slight change in the way of signing, which can affect change in the value of global features. In this case the effectiveness of the signature verification also changes (decreases). The possibility of predicting the values of global features can result in a partial elimination of the described problem. Tests of the proposed method were performed using ATVS-SLT DB database of the dynamic signatures.

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

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Titel: A Method for Changes Prediction of the Dynamic Signature Global Features over Time
verfasst von: Marcin Zalasiński
Krystian Łapa
Krzysztof Cpałka
Takamichi Saito
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_68

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