Robust watermarking using hand gesture for enhanced authentication

According to Bell Lab�s finding, a large percentage of passwords chosen by users were easy to decode in a short period of time. As users realize the importance of security and privacy, there is a rapid increment of higher security demand in authentication systems. In this work, a gesture authentic...

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Main Authors: Seng, W.C., Fong, L.L., Shing, N.L., Noudeh, S.A.H.
Format: Article
Published: 2011
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Online Access:http://eprints.um.edu.my/5414/
http://ejum.fsktm.um.edu.my/article/1062.pdf
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Institution: Universiti Malaya
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spelling my.um.eprints.54142013-04-05T02:00:19Z http://eprints.um.edu.my/5414/ Robust watermarking using hand gesture for enhanced authentication Seng, W.C. Fong, L.L. Shing, N.L. Noudeh, S.A.H. T Technology (General) According to Bell Lab�s finding, a large percentage of passwords chosen by users were easy to decode in a short period of time. As users realize the importance of security and privacy, there is a rapid increment of higher security demand in authentication systems. In this work, a gesture authentication system built with a robust watermark algorithm is presented. This biometric authentication system is divided into two modules, which are watermark embedding module and watermark detection module. For watermark embedding module, the first level of DWT is applied to the host image. Hand gesture image (watermark) is embedded into a host image using LSB and the redundant embedding method. For watermark detection module, the watermarked image will be processed and the majority voting method is used to retrieve the watermark from watermarked image. Non-blind watermarking is emphasized in watermark detection module. Various tests have been evaluated in both modules. Firstly, the effectiveness and fidelity tests are evaluated for watermark embedding module and both results are pass. Secondly, all the detection effectiveness test (pass) and robustness test using JPEG Compression (98.34), Gaussian Noise (98.34), Median Filtering (85.48) and Contrast Adjustment (98.34) have satisfying results. As conclusion, this algorithm is suitable to be applied in any type of image authentication system. 2011 Article PeerReviewed Seng, W.C. and Fong, L.L. and Shing, N.L. and Noudeh, S.A.H. (2011) Robust watermarking using hand gesture for enhanced authentication. Malaysian Journal of Computer Science, 24 (2). p. 98. ISSN 0127-9084 http://ejum.fsktm.um.edu.my/article/1062.pdf
institution Universiti Malaya
building UM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaya
content_source UM Research Repository
url_provider http://eprints.um.edu.my/
topic T Technology (General)
spellingShingle T Technology (General)
Seng, W.C.
Fong, L.L.
Shing, N.L.
Noudeh, S.A.H.
Robust watermarking using hand gesture for enhanced authentication
description According to Bell Lab�s finding, a large percentage of passwords chosen by users were easy to decode in a short period of time. As users realize the importance of security and privacy, there is a rapid increment of higher security demand in authentication systems. In this work, a gesture authentication system built with a robust watermark algorithm is presented. This biometric authentication system is divided into two modules, which are watermark embedding module and watermark detection module. For watermark embedding module, the first level of DWT is applied to the host image. Hand gesture image (watermark) is embedded into a host image using LSB and the redundant embedding method. For watermark detection module, the watermarked image will be processed and the majority voting method is used to retrieve the watermark from watermarked image. Non-blind watermarking is emphasized in watermark detection module. Various tests have been evaluated in both modules. Firstly, the effectiveness and fidelity tests are evaluated for watermark embedding module and both results are pass. Secondly, all the detection effectiveness test (pass) and robustness test using JPEG Compression (98.34), Gaussian Noise (98.34), Median Filtering (85.48) and Contrast Adjustment (98.34) have satisfying results. As conclusion, this algorithm is suitable to be applied in any type of image authentication system.
format Article
author Seng, W.C.
Fong, L.L.
Shing, N.L.
Noudeh, S.A.H.
author_facet Seng, W.C.
Fong, L.L.
Shing, N.L.
Noudeh, S.A.H.
author_sort Seng, W.C.
title Robust watermarking using hand gesture for enhanced authentication
title_short Robust watermarking using hand gesture for enhanced authentication
title_full Robust watermarking using hand gesture for enhanced authentication
title_fullStr Robust watermarking using hand gesture for enhanced authentication
title_full_unstemmed Robust watermarking using hand gesture for enhanced authentication
title_sort robust watermarking using hand gesture for enhanced authentication
publishDate 2011
url http://eprints.um.edu.my/5414/
http://ejum.fsktm.um.edu.my/article/1062.pdf
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