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Title:A biometric authentication model using hand gesture images
Authors:ID Fong, Simon (Author)
ID Zhuang, Yan (Author)
ID Fister, Iztok (Author)
ID Fister, Iztok (Author)
Files:.pdf BioMedical_Engineering_OnLine_2013_Fong_et_al._A_biometric_authentication_model_using_hand_gesture_images.pdf (1,83 MB)
MD5: 5D182D45E604C1E634BCD7FFE341D76F
 
URL http://biomedical-engineering-online.biomedcentral.com/articles/10.1186/1475-925X-12-111
 
Language:English
Work type:Scientific work
Typology:1.01 - Original Scientific Article
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:A novel hand biometric authentication method based on measurements of the user's stationary hand gesture of hand sign language is proposed. The measurement of hand gestures could be sequentially acquired by a low-cost video camera. There could possibly be another level of contextual information,associated with these hand signs to be used in biometric authentication. As an analogue, instead of typing a password 'iloveu' in text which is relatively vulnerable over a communication network, a signer can encode a biometric password using a sequence of hand signs, 'i', 'l', 'o', 'v', 'e', and 'u'. Subsequently the features from the hand gesture images are extracted which are integrally fuzzy in nature, to be recognized by a classification model for telling if this signer is who he claimed himself to be, by examining over his hand shape and the postures in doing those signs. Itis believed that everybody has certain slight but unique behavioral characteristics in sign language, so are the different hand shape compositions. Simple and efficient image processing algorithms are used in hand sign recognition, including intensity profiling, color histogram and dimensionality analysis, coupled with several popular machine learning algorithms. Computer simulation is conducted for investigating the efficacy ofthis novel biometric authentication model which shows up to 93.75% recognition accuracy.
Keywords:biometric authentication, hand gesture, hand sign recognition, machine learning
Publication status:Published
Publication version:Version of Record
Year of publishing:2013
Number of pages:str. 1-26
Numbering:Letn. 12
PID:20.500.12556/DKUM-66482 New window
ISSN:1475-925X
UDC:004.8
ISSN on article:1475-925X
COBISS.SI-ID:17279254 New window
DOI:10.1186/1475-925X-12-111 New window
NUK URN:URN:SI:UM:DK:GACTATZV
Publication date in DKUM:28.06.2017
Views:1682
Downloads:466
Metadata:XML DC-XML DC-RDF
Categories:Misc.
:
FONG, Simon, ZHUANG, Yan, FISTER, Iztok and FISTER, Iztok, 2013, A biometric authentication model using hand gesture images. BioMedical Engineering Online [online]. 2013. Vol. 12, p. 1–26. [Accessed 27 April 2025]. DOI 10.1186/1475-925X-12-111. Retrieved from: https://dk.um.si/IzpisGradiva.php?lang=eng&id=66482
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Record is a part of a journal

Title:BioMedical Engineering Online
Shortened title:Biomed. Eng. Online
Publisher:BioMed Central
ISSN:1475-925X
COBISS.SI-ID:6029396 New window

Licences

License:CC BY 4.0, Creative Commons Attribution 4.0 International
Link:http://creativecommons.org/licenses/by/4.0/
Description:This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.
Licensing start date:28.06.2017

Secondary language

Language:Slovenian
Keywords:biometrična avtentikacija, kretnje rok, prepoznavanje kretenj, znakovni jezik, strojno učenje


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