Blind 3D-Printing Watermarking Using Moment Alignment and Surface Norm Distribution Article Swipe
Arnaud Delmotte
,
Kenichiro Tanaka
,
Hiroyuki Kubo
,
Takuya Funatomi
,
Yasuhiro Mukaigawa
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1109/tmm.2020.3025660
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1109/tmm.2020.3025660
The recent development of 3D printing technology has brought concerns about its potential misuse, such as in copyright infringement and crimes.Although there have been many studies on blind 3D mesh watermarking for the copyright protection of digital objects, methods applicable to 3D printed objects are rare.In this paper, we propose a novel blind watermarking algorithm for 3D printed objects with applications for copyright protection, traitor tracing, object identification, and crime investigation.Our method allows us to embed a few bits of data into a 3D-printed object and retrieve it by 3D scanning without requiring any information about the original mesh.The payload is embedded on the object's surface by slightly modifying the distribution of surface norms, that is, the distance between the surface and the center of gravity.It is robust to resampling and can work with any 3D printer and scanner technology.In addition, our method increases the capacity and resistance by subdividing the mesh into a set of bins and spreading the data over the entire surface to negate the effect of local printing artifacts.The method's novelties include extending the vertex norm histogram to a continuous surface and the use of 3D moments to synchronize a watermark signal in a 3Dprinting context.In the experiments, our method was evaluated using a public dataset against center, orientation, minimum and maximum norm misalignments; a printing simulation; and actual print/scan experiments using a standard 3D printer and scanner.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1109/tmm.2020.3025660
- https://ieeexplore.ieee.org/ielx7/6046/4456689/09204429.pdf
- OA Status
- hybrid
- Cited By
- 17
- References
- 51
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3088984785
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3088984785Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1109/tmm.2020.3025660Digital Object Identifier
- Title
-
Blind 3D-Printing Watermarking Using Moment Alignment and Surface Norm DistributionWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2020Year of publication
- Publication date
-
2020-09-22Full publication date if available
- Authors
-
Arnaud Delmotte, Kenichiro Tanaka, Hiroyuki Kubo, Takuya Funatomi, Yasuhiro MukaigawaList of authors in order
- Landing page
-
https://doi.org/10.1109/tmm.2020.3025660Publisher landing page
- PDF URL
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https://ieeexplore.ieee.org/ielx7/6046/4456689/09204429.pdfDirect link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
hybridOpen access status per OpenAlex
- OA URL
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https://ieeexplore.ieee.org/ielx7/6046/4456689/09204429.pdfDirect OA link when available
- Concepts
-
Computer science, Digital watermarking, Watermark, Computer vision, 3D printing, Scanner, Histogram, Artificial intelligence, Computer graphics (images), Norm (philosophy), Image (mathematics), Engineering, Law, Mechanical engineering, Political scienceTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
17Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 4, 2024: 3, 2023: 5, 2022: 2, 2021: 3Per-year citation counts (last 5 years)
- References (count)
-
51Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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