<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>The growing amount of collected and processed data means that there is a need to control access to these resources. Very often, this type of control is carried out on the basis of bio-metric analysis. The article proposes a new user authentication method based on a spatial analysis of the movement of the finger’s position. This movement creates a sequence of data that is registered by a motion recording device. The presented approach combines spatial analysis of the position of all fingers at the time. The proposed method is able to use the specific, often different movements of fingers of each user. The experimental results confirm the effectiveness of the method in biometric applications. In this paper, we also introduce an effective method of feature selection, based on the Hotelling T<sup>2</sup> statistic. This approach allows selecting the best distinctive features of each object from a set of all objects in the database. It is possible thanks to the appropriate preparation of the input data.</p>
</abstract>

The growing amount of collected and processed data means that there is a need to control access to these resources. Very often, this type of control is carried out on the basis of bio-metric analysis. The article proposes a new user authentication method based on a spatial analysis of the movement of the finger’s position. This movement creates a sequence of data that is registered by a motion recording device. The presented approach combines spatial analysis of the position of all fingers at the time. The proposed method is able to use the specific, often different movements of fingers of each user. The experimental results confirm the effectiveness of the method in biometric applications. In this paper, we also introduce an effective method of feature selection, based on the Hotelling T2 statistic. This approach allows selecting the best distinctive features of each object from a set of all objects in the database. It is possible thanks to the appropriate preparation of the input data.

A New Hand-Movement-Based Authentication Method Using Feature Importance Selection with the Hotelling’s Statistic

Institute of Computer Science, Faculty of Science and Technology

Journal of Artificial Intelligence and Soft Computing Research

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

The growing amount of collected and processed data means that there is a need to control access to these resources. Very often, this type of control is carried...

A New Hand-Movement-Based Authentication Method Using Feature Importance Selection with the Hotelling’s Statistic

Online veröffentlicht: 08. Okt. 2021

Seitenbereich: 41 - 59

Eingereicht: 26. März 2021

Akzeptiert: 02. Juli 2021

DOI: https://doi.org/10.2478/jaiscr-2022-0004

Schlüsselwörter
biometrics, person authentication, feature selection, Hotelling’s statistic

© 2022 Rafal Doroz et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

A New Hand-Movement-Based Authentication Method Using Feature Importance Selection with the Hotelling’s Statistic

Online veröffentlicht: 08. Okt. 2021

Seitenbereich: 41 - 59

Eingereicht: 26. März 2021

Akzeptiert: 02. Juli 2021

DOI: https://doi.org/10.2478/jaiscr-2022-0004

Schlüsselwörterbiometrics, person authentication, feature selection, Hotelling’s statistic

© 2022 Rafal Doroz et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Schlüsselwörter
biometrics, person authentication, feature selection, Hotelling’s statistic