Blind Image Watermark Detection Algorithm Based on Discrete Shearlet Transform Using Statistical Decision Theory
- Submitting institution
-
University of Derby
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 785317-1
- Type
- D - Journal article
- DOI
-
10.1109/TCI.2018.2794065
- Title of journal
- IEEE Transactions on Computational Imaging
- Article number
- -
- First page
- 46
- Volume
- 4
- Issue
- 1
- ISSN
- 2333-9403
- Open access status
- Compliant
- Month of publication
- -
- Year of publication
- 2018
- URL
-
http://ieeexplore.ieee.org/document/8259288/
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
3
- Research group(s)
-
-
- Citation count
- 23
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This is the first paper proposing to use Shearlet transform in blind watermarking to protect multimedia IP. The ownership information is embedded into multimedia pixels using Shearlet Transform satisfying robustness and invisibility requirements. A novel approach was presented, tested using a large dataset, compared with and outperforms the counterparts. Prof Kurugollu was awarded a RAEng Industrial Fellowship (ISS1617-45) with Titan IC Systems Ltd. to take this research developed in this paper further into DPI systems. This helped Titan IC Systems to diversify its product portfolio, facilitating a successful acquisition by NVIDIA, which is the world leader in SoC and GPU.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
