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Single Image Watermark Retrieval from 3D Printed Surfaces via Convolutional Neural Networks

Zhang, Xin; Wang, Qian; Ivrissimtzis, Ioannis

Single Image Watermark Retrieval from 3D Printed Surfaces via Convolutional Neural Networks Thumbnail


Authors

Xin Zhang

Qian Wang



Contributors

Gary Tam
Editor

Franck Vidal
Editor

Abstract

In this paper we propose and analyse a method for watermarking 3D printed objects, concentrating on the watermark retrieval problem. The method embeds the watermark in a planar region of the 3D printed object in the form of small semi-spherical or cubic bumps arranged at the nodes of a regular grid. The watermark is extracted from a single image of the watermarked planar region through a Convolutional Neural Network. Experiments with 3D printed objects, produced by filaments of various colours, show that in most cases the retrieval method has a high accuracy rate.

Citation

Zhang, X., Wang, Q., & Ivrissimtzis, I. (2018). Single Image Watermark Retrieval from 3D Printed Surfaces via Convolutional Neural Networks. In G. Tam, & F. Vidal (Eds.), Computer Graphics & Visual Computing (CGVC) 2018 : Eurographics UK Chapter proceedings (117-120). https://doi.org/10.2312/cgvc.20182019

Conference Name EG UK Computer Graphics & Visual Computing
Conference Location Swansea, UK
Acceptance Date Jul 24, 2018
Publication Date Jan 1, 2018
Deposit Date Nov 20, 2018
Publicly Available Date Mar 29, 2024
Pages 117-120
Book Title Computer Graphics & Visual Computing (CGVC) 2018 : Eurographics UK Chapter proceedings.
DOI https://doi.org/10.2312/cgvc.20182019
Public URL https://durham-repository.worktribe.com/output/1143548
Publisher URL http://diglib.eg.org/handle/10.2312/cgvc20182019

Files

Accepted Conference Proceeding (3.7 Mb)
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Copyright Statement
This is the accepted version of the following article: Zhang, Xin , Wang, Qian & Ivrissimtzis, Ioannis (2018), Single Image Watermark Retrieval from 3D Printed Surfaces via Convolutional Neural Networks, in Tam, Gary & Vidal, Franck eds, EG UK Computer Graphics & Visual Computing. Swansea, UK, Eurographics Association, Goslar, Germany, 117-120 which has been published in final form at https://doi.org/10.2312/cgvc.20182019





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