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A Novel Secure and Robust Image Watermarking Method Based on Decorrelation of Channels, Singular Vectors, and ValuesIMRAN, M. , HARVEY, B. A. |
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Author keywords
authentication, data security, image decomposition, image forensic, watermarking
References keywords
watermarking(16), image(14), digital(13), processing(10), scheme(8), signal(7), singular(6), decomposition(6), jdsp(5), transform(4)
Blue keywords are present in both the references section and the paper title.
About this article
Date of Publication: 2017-11-30
Volume 17, Issue 4, Year 2017, On page(s): 107 - 116
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2017.04013
Web of Science Accession Number: 000417674300013
SCOPUS ID: 85035807013
Abstract
A novel secure and robust image watermarking technique for color images is presented in this paper. Besides robustness and imperceptibility (which are the most important requisites of any watermarking scheme), there are two other challenges a good watermarking scheme must meet: security and capacity. Therefore, in devising the presented scheme, special consideration is also given to above-mentioned requirements. In order to do so, principal component analysis is involved to enhance imperceptibility and the unique utilization of singular value decomposition is done to achieve better performance in regard to capacity and robustness. Finally, a novel method is proposed to select constituents of an image for watermark embedding, which further improves the security. As a consequence, four essential requisites of a good watermarking scheme are achieved as visible from experimental results. To measure the behavior of presented watermarking scheme, a number of experiments were conducted by utilizing several color images as host images and as watermarks. The presented technique is compared with the latest available watermarking techniques and attained better results than them. |
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[CrossRef] [Web of Science Times Cited 41] [SCOPUS Times Cited 51] Web of Science® Citations for all references: 1,918 TCR SCOPUS® Citations for all references: 3,792 TCR Web of Science® Average Citations per reference: 83 ACR SCOPUS® Average Citations per reference: 165 ACR TCR = Total Citations for References / ACR = Average Citations per Reference We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more Citations for references updated on 2024-12-16 20:11 in 149 seconds. Note1: Web of Science® is a registered trademark of Clarivate Analytics. Note2: SCOPUS® is a registered trademark of Elsevier B.V. Disclaimer: All queries to the respective databases were made by using the DOI record of every reference (where available). Due to technical problems beyond our control, the information is not always accurate. Please use the CrossRef link to visit the respective publisher site. |
Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
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