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Security and Communication Networks
Article . 2016 . Peer-reviewed
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https://doi.org/10.4108/icst.b...
Article . 2015 . Peer-reviewed
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A 3‐D hand gesture signature based biometric authentication system for smartphones

Authors: Ziwen Sun; Yao Wang; Gang Qu 0001; Zhiping Zhou;

A 3‐D hand gesture signature based biometric authentication system for smartphones

Abstract

AbstractThe authentication mechanism being equipped in most of the smartphones, by detecting a 4‐digit password or a simple pattern, are easy to be hacked and impersonated. In this paper, a 3‐D hand gesture signature (HGS) based biometric authentication system is designed and implemented by taking advantage of the on‐phone accelerometer to capture the 3‐D acceleration information when user makes a gesture to gain access to the phone. The captured data will be processed through a sequence of signal processing such as data smooth, gesture spotting, sequence alignment, and interpolation, and then a match rule will be used to compare the processed data and the genuine user's registered pattern to determine whether granting the access to the phone to the user. And an automatic template updating strategy based on cluster analysis is proposed to improve the stability of the system. The 3‐D HGS authentication system has been implemented on real smartphones, and the results tested for a total of 76 520 times by 19 users show very low false acceptance (0.27%) and false rejection rates (4.65%). Furthermore, comparison tests have been carried out among the 3‐D HGS and two similar authentication systems by exporting the real gesture samples from the phones to a desktop PC, the simulation results reveal the 3‐D HGS system has the best authentication accuracy. Copyright © 2016 John Wiley & Sons, Ltd.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
29
Top 10%
Top 10%
Average
gold