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Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12128/21789
Title: A New Hand-Movement-Based Authentication Method Using Feature Importance Selection with the Hotelling’s Statistic
Authors: Doroz, Rafał
Wróbel, Krzysztof
Porwik, Piotr
Orczyk, Tomasz
Keywords: biometrics; person authentication; feature selection; Hotelling’s statistic
Issue Date: 2022
Citation: "Journal of Artificial Intelligence and Soft Computing Research" 2022, iss. 1, s. 41-59
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 biometric 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.
URI: http://hdl.handle.net/20.500.12128/21789
DOI: 10.2478/jaiscr-2022-0004
ISSN: 2449-6499
Appears in Collections:Artykuły (WNŚiT)

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