Local feature based geometric-resistant image information hiding

Gao, X; Deng, C; Li, X; Tao, D

Local feature based geometric-resistant image information hiding

Gao, X Deng, C Li, X Tao, D

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Publication Type:: Journal Article
Citation:: Cognitive Computation, 2010, 2 (2), pp. 68 - 77
Issue Date:: 2010-06-01

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Field	Value	Language
dc.contributor.author	Gao, X	en_US
dc.contributor.author	Deng, C	en_US
dc.contributor.author	Li, X	en_US
dc.contributor.author	Tao, D https://orcid.org/0000-0001-7225-5449	en_US
dc.date.issued	2010-06-01	en_US
dc.identifier.citation	Cognitive Computation, 2010, 2 (2), pp. 68 - 77	en_US
dc.identifier.issn	1866-9956	en_US
dc.identifier.uri	http://hdl.handle.net/10453/15230
dc.description.abstract	Watermarking aims to hide particular information into some carrier but does not change the visual cognition of the carrier itself. Local features are good candidates to address the watermark synchronization error caused by geometric distortions and have attracted great attention for content-based image watermarking. This paper presents a novel feature point-based image watermarking scheme against geometric distortions. Scale invariant feature transform (SIFT) is first adopted to extract feature points and to generate a disk for each feature point that is invariant to translation and scaling. For each disk, orientation alignment is then performed to achieve rotation invariance. Finally, watermark is embedded in middle-frequency discrete Fourier transform (DFT) coefficients of each disk to improve the robustness against common image processing operations. Extensive experimental results and comparisons with some representative image watermarking methods confirm the excellent performance of the proposed method in robustness against various geometric distortions as well as common image processing operations. © Springer Science+Business Media, LLC 2010.	en_US
dc.relation.ispartof	Cognitive Computation	en_US
dc.relation.isbasedon	10.1007/s12559-010-9033-8	en_US
dc.title	Local feature based geometric-resistant image information hiding	en_US
dc.type	Journal Article
utslib.citation.volume	2	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
utslib.for	1109 Neurosciences	en_US
utslib.for	1702 Cognitive Sciences	en_US
dc.location.activity	San Diego, USA
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
utslib.copyright.status	closed_access
pubs.issue	2	en_US
pubs.publication-status	Published	en_US
pubs.volume	2	en_US

Abstract:

Watermarking aims to hide particular information into some carrier but does not change the visual cognition of the carrier itself. Local features are good candidates to address the watermark synchronization error caused by geometric distortions and have attracted great attention for content-based image watermarking. This paper presents a novel feature point-based image watermarking scheme against geometric distortions. Scale invariant feature transform (SIFT) is first adopted to extract feature points and to generate a disk for each feature point that is invariant to translation and scaling. For each disk, orientation alignment is then performed to achieve rotation invariance. Finally, watermark is embedded in middle-frequency discrete Fourier transform (DFT) coefficients of each disk to improve the robustness against common image processing operations. Extensive experimental results and comparisons with some representative image watermarking methods confirm the excellent performance of the proposed method in robustness against various geometric distortions as well as common image processing operations. © Springer Science+Business Media, LLC 2010.

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http://hdl.handle.net/10453/15230