The DOI matches its Crossref record; 36 of the 70 references it cites were found in a registry or an index.
Secure spread spectrum watermarking for multimedia
Abstract
This paper presents a secure (tamper-resistant) algorithm for watermarking images, and a methodology for digital watermarking that may be generalized to audio, video, and multimedia data. We advocate that a watermark should be constructed as an independent and identically distributed (i.i.d.) Gaussian random vector that is imperceptibly inserted in a spread-spectrum-like fashion into the perceptually most significant spectral components of the data. We argue that insertion of a watermark under this regime makes the watermark robust to signal processing operations (such as lossy compression, filtering, digital-analog and analog-digital conversion, requantization, etc.), and common geometric transformations (such as cropping, scaling, translation, and rotation) provided that the original image is available and that it can be successfully registered against the transformed watermarked image. In these cases, the watermark detector unambiguously identifies the owner. Further, the use of Gaussian noise, ensures strong resilience to multiple-document, or collusional, attacks. Experimental results are provided to support these claims, along with an exposition of pending open problems.
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Metadata
- Authors
- Cox, I. J., Kilian, J., Leighton, F. T., & Shamoon, T.
- Affiliations
- NEC (Japan) (JP)
- Massachusetts Institute of Technology (US)
- ORCID
- Cox, I.J.
- Venue
- IEEE Transactions on Image Processing
- Published
- 1997-12
- Volume
- 6
- Issue
- 12
- Pages
- 1673-1687
- ISSN
- 1057-7149 (ISSN-L)
- 1941-0042
- OpenAlex
- W2116467012
- Semantic Scholar
- a5eaa0b77d774745409499be2a2f16c506156161
- Cited by
- 5,299
- References
- 70
- Citations by year
- 2026: 65 · 2025: 60 · 2024: 48 · 2023: 69 · 2022: 74 · 2021: 85 · 2020: 84 · 2019: 112 · 2018: 132 · 2017: 160 · 2016: 168 · 2015: 201 · 2014: 211 · 2013: 240 · 2012: 289
- FWCI
- 98.40
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Transactions on Image Processing (publishedVersion)
- PubMed (publishedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Steganography and Watermarking Techniques
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Digital Media Forensic Detection
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Data Compression Techniques
- Keywords
- digital watermarking, spread spectrum watermarking, tamper resistance, Gaussian random vectors, image watermarking, watermark robustness, lossy compression, geometric transformations, image registration
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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