Al-Khafaji, H. and Abhayaratne, C. orcid.org/0000-0002-2799-7395 (2019) Graph spectral domain blind watermarking. In: ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). ICASSP 2019, 12-17 May 2019, Brighton, United Kingdom. IEEE , pp. 2492-2496. ISBN 978-1-4799-8131-1
Abstract
This paper proposes the first ever graph spectral domain blind watermarking algorithm. We explore the recently developed graph signal processing for spread-spectrum watermarking to authenticate the data recorded on non-Cartesian grids, such as sensor data, 3D point clouds, Lidar scans and mesh data. The choice of coefficients for embedding the watermark is driven by the model for minimisation embedding distortion and the robustness model. The distortion minimisation model is proposed to reduce the watermarking distortion by establishing the relationship between the error distortion using mean square error and the selected Graph Fourier coefficients to embed the watermark. The robustness model is proposed to improve the watermarking robustness against the attacks by establishing the relationship between the watermark extraction and the effect of the attacks, namely, additive noise and nodes data deletion. The proposed models were verified by the experimental results.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. Reproduced in accordance with the publisher's self-archiving policy. |
Keywords: | Graph spectral domain blind watermarking; Graph Fourier Transform (GFT); robustness; distortion |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Electronic and Electrical Engineering (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 10 May 2019 15:08 |
Last Modified: | 17 Apr 2020 00:39 |
Status: | Published |
Publisher: | IEEE |
Refereed: | Yes |
Identification Number: | 10.1109/icassp.2019.8683753 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:145959 |