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Single image watermark retrieval from 3D printed surfaces via convolutional neural networks.

Zhang, Xin and Wang, Qian and Ivrissimtzis, Ioannis (2018) 'Single image watermark retrieval from 3D printed surfaces via convolutional neural networks.', in Computer Graphics & Visual Computing (CGVC) 2018 : Eurographics UK Chapter proceedings. Goslar, Germany: Eurographics Association, pp. 117-120.


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.

Item Type:Book chapter
Full text:(AM) Accepted Manuscript
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Publisher 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
Date accepted:24 July 2018
Date deposited:21 November 2018
Date of first online publication:2018
Date first made open access:No date available

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