Blind Watermarking for 3-D Printed Objects using Surface Norm Distribution

Delmotte, Arnaud; Tanaka, Kenichiro; Kubo, Hiroyuki; Funatomi, Takuya; Mukaigawa, Yasuhiro

doi:10.1109/iciev.2018.8640986

Cited by 8 publications

(8 citation statements)

References 8 publications

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“…• Persistence of the watermark signal in duplicated objects. This paper extends our conference paper [12] that proposed a blind watermarking method robust to the print/scan process and based on the vertex norm watermarking technique [13], [14]. We extend our previous method with the following improvements.…”

Section: Introductionmentioning

confidence: 65%

“…In practice, the watermark had low visibility on our printed objects except 1 Standard FDM printers have a precision of approximately 0.1mm, and other technologies such as SLA are even higher precision Fig. 20: Comparison between the original vertex norm watermarking method [13], [14], our previous work on surface norm watermarking [12], and the proposed method.…”

Section: Discussion and Future Workmentioning

confidence: 99%

“…The proposed method is an extension of our previous paper [12], which was based on the 3D mesh watermarking method from Cho et al [13], [14], that used a distribution of vertex norms. Cho et al's method was developed for digital data with a mesh structure, not for the print/scan scenario.…”

Section: Core Ideas Of the Proposed Methodsmentioning

confidence: 99%

“…To evaluate the improvement made by this paper, we compared our method with our previous work [12] and with the original vertex norm watermarking [13], [14]. To obtain reliable results, we evaluated with a printing simulation using the recommended parameters on the complete dataset with 5 different watermarks per model.…”

Section: H Comparison To the Previous Workmentioning

confidence: 99%

See 3 more Smart Citations

Blind 3D-Printing Watermarking Using Moment Alignment and Surface Norm Distribution

Delmotte¹,

Tanaka²,

Kubo³

et al. 2021

IEEE Trans. Multimedia

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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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Section: Introductionmentioning

confidence: 65%

Section: Discussion and Future Workmentioning

confidence: 99%

Section: Core Ideas Of the Proposed Methodsmentioning

confidence: 99%

Section: H Comparison To the Previous Workmentioning

confidence: 99%

See 2 more Smart Citations

Blind 3D-Printing Watermarking Using Moment Alignment and Surface Norm Distribution

Delmotte¹,

Tanaka²,

Kubo³

et al. 2021

IEEE Trans. Multimedia

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“…We developed a blind watermarking method [26] that is retrievable from a full 3D scan and resistant to reprinting but has stronger deformation and is not resistant to cropping or non-uniform deformation. The current application scenario is different from that in our previous paper, which assumed that we attempted the extraction from a standard 3D scan that could be created by someone else without following a precise procedure, whereas the present paper supposes that the user will follow our procedure, that is, the person that performs the scan is the person that is attempting to extract the watermark.…”

Section: Related Workmentioning

confidence: 99%

Blind Watermarking for 3-D Printed Objects by Locally Modifying Layer Thickness

Delmotte

Tanaka

Kubo

et al. 2020

IEEE Trans. Multimedia

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We propose a new blind watermarking algorithm for three-dimensional (3D) printed objects that has applications in metadata embedding, robotic grasping, counterfeit prevention, and crime investigation. Our method can be used on fused deposition modeling (FDM) 3D printers and works by modifying the printed layer thickness on small patches of the surface of an object. These patches can be applied to multiple regions of the object, thereby making it resistant to various attacks such as cropping, local deformation, local surface degradation, or printing errors. The novelties of our method are the use of the thickness of printed layers as a one-dimensional carrier signal to embed data, the minimization of distortion by only modifying the layers locally, and one-shot detection using a common paper scanner. To correct encoding or decoding errors, our method combines multiple patches and uses a two-dimensional (2D) parity check to estimate the error probability of each bit to obtain a higher correction rate than a naive majority vote. The parity bits included in the patches have a double purpose because, in addition to error detection, they are also used to identify the orientation of the patches. In our experiments, we successfully embedded a watermark into flat surfaces of 3D objects with various filament colors using a standard FDM 3D printer, extracted it using a common 2D paper scanner and evaluated the sensitivity to surface degradation and signal amplitude.

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Innovative Technologies for Virtual Museums: An Overview

Furferi

2022

Communications in Computer and Information Science

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Blind Watermarking for 3-D Printed Objects using Surface Norm Distribution

Cited by 8 publications

References 8 publications

Blind 3D-Printing Watermarking Using Moment Alignment and Surface Norm Distribution

Blind 3D-Printing Watermarking Using Moment Alignment and Surface Norm Distribution

Blind Watermarking for 3-D Printed Objects by Locally Modifying Layer Thickness

Innovative Technologies for Virtual Museums: An Overview

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