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Title: In-air signature verification system using Leap Motion
Authors: Guerra Segura, Elyoenai 
Ortega-Pérez, Aysse
Travieso, Carlos M. 
UNESCO Clasification: 3307 Tecnología electrónica
Keywords: 3D Signature Processing
3D Signature Verification/Recognition
In-Air Signatures
Leap Motion Controller
Machine Learning
Issue Date: 2020
Journal: Expert Systems with Applications 
Abstract: Signature verification is a widely explored field due to its high acceptance and its compromise between security and comfort. Recently, different techniques have appeared to improve the capture, processing, and classification of signatures. In this work, authors present a novel and robust in-air signature verification system, which applies the use of Leap Motion controller to characterize in-air strokes, due to its stability and good performance for this task, as it will be demonstrated. Therefore, a database has been built for developing the experiments, which is composed of 100 users, with 10 genuine and 10 forgery samples per user. The implemented system is tested against two tests of impostor samples, zero effort attacks and active impostors. The second type of attacks are developed by different users, who showed very good abilities with the sensor. The classification is done by a Least Square Support Vector Machine. The equal error rate was 0.25% and 1.20%, respectively. The proposed system achieves very good results in comparison with the state-of-the-art one, which suggests that in-air signature processing gives an opportunity to increase systems’ security.
ISSN: 0957-4174
DOI: 10.1016/j.eswa.2020.113797
Source: Expert Systems with Applications[ISSN 0957-4174],v. 165, (Marzo 2021)
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