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

IF 3.3 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Journal of Artificial Intelligence and Soft Computing Research Pub Date : 2021-10-08 DOI:10.2478/jaiscr-2022-0004
R. Doroz, K. Wrobel, P. Porwik, T. Orczyk
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引用次数: 2

Abstract

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.
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基于Hotelling统计特征重要性选择的手部动作认证新方法
收集和处理的数据量越来越大,这意味着需要控制对这些资源的访问。通常,这种类型的控制是在生物识别分析的基础上进行的。本文提出了一种新的基于手指位置运动空间分析的用户认证方法。这个动作产生一系列的数据,这些数据被动作记录设备记录下来。所提出的方法结合了所有手指在同一时间的位置空间分析。所提出的方法能够使用每个用户特定的,通常不同的手指运动。实验结果证实了该方法在生物识别应用中的有效性。本文还介绍了一种有效的基于Hotelling T2统计量的特征选择方法。这种方法允许从数据库中所有对象的集合中选择每个对象的最佳独特特征。由于输入数据的适当准备,这是可能的。
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来源期刊
Journal of Artificial Intelligence and Soft Computing Research
Journal of Artificial Intelligence and Soft Computing Research COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-
CiteScore
7.00
自引率
25.00%
发文量
10
审稿时长
24 weeks
期刊介绍: Journal of Artificial Intelligence and Soft Computing Research (available also at Sciendo (De Gruyter)) is a dynamically developing international journal focused on the latest scientific results and methods constituting traditional artificial intelligence methods and soft computing techniques. Our goal is to bring together scientists representing both approaches and various research communities.
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