Computer vision approach in monitoring for illicit and copyrighted objects in digital manufacturing
We propose a monitoring system for detecting illicit and copyrighted objects in digital manufacturing (DM). Our system is based on extracting and analyzing high-dimensional data from blueprints of three-dimensional (3D) objects. We aim to protect the legal interests of DM service providers, who may...
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sg-ntu-dr.10356-1789262024-07-12T15:40:05Z Computer vision approach in monitoring for illicit and copyrighted objects in digital manufacturing Volkau, Ihar Krasovskii, Sergei Mujeeb, Abdul Balinsky, Helen School of Electrical and Electronic Engineering HP–NTU Digital Manufacturing Corporate Lab Engineering Computer vision High-dimensional data We propose a monitoring system for detecting illicit and copyrighted objects in digital manufacturing (DM). Our system is based on extracting and analyzing high-dimensional data from blueprints of three-dimensional (3D) objects. We aim to protect the legal interests of DM service providers, who may receive requests for 3D printing from external sources, such as emails or uploads. Such requests may contain blueprints of objects that are illegal, restricted, or otherwise controlled in the country of operation or protected by copyright. Without a reliable way to identify such objects, the service provider may unknowingly violate the laws and regulations and face legal consequences. Therefore, we propose a multi-layer system that automatically detects and flags such objects before the 3D printing process begins. We present efficient computer vision algorithms for object analysis and scalable system architecture for data storage and processing and explain the rationale behind the suggested system architecture. Agency for Science, Technology and Research (A*STAR) Published version This study is supported under the RIE2020 Industry Alignment Fund—Industry Collaboration Projects (IAF-ICP) Funding Initiative, as well as by cash and in-kind contributions from industry partner HP Inc. through the HP-NTU Digital Manufacturing Corporate Lab. 2024-07-10T05:46:39Z 2024-07-10T05:46:39Z 2024 Journal Article Volkau, I., Krasovskii, S., Mujeeb, A. & Balinsky, H. (2024). Computer vision approach in monitoring for illicit and copyrighted objects in digital manufacturing. Computers, 13(4), 90-. https://dx.doi.org/10.3390/computers13040090 2073-431X https://hdl.handle.net/10356/178926 10.3390/computers13040090 2-s2.0-85191444408 4 13 90 en IAF-ICP Computers © 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). application/pdf |
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Engineering Computer vision High-dimensional data Volkau, Ihar Krasovskii, Sergei Mujeeb, Abdul Balinsky, Helen Computer vision approach in monitoring for illicit and copyrighted objects in digital manufacturing |
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We propose a monitoring system for detecting illicit and copyrighted objects in digital manufacturing (DM). Our system is based on extracting and analyzing high-dimensional data from blueprints of three-dimensional (3D) objects. We aim to protect the legal interests of DM service providers, who may receive requests for 3D printing from external sources, such as emails or uploads. Such requests may contain blueprints of objects that are illegal, restricted, or otherwise controlled in the country of operation or protected by copyright. Without a reliable way to identify such objects, the service provider may unknowingly violate the laws and regulations and face legal consequences. Therefore, we propose a multi-layer system that automatically detects and flags such objects before the 3D printing process begins. We present efficient computer vision algorithms for object analysis and scalable system architecture for data storage and processing and explain the rationale behind the suggested system architecture. |
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School of Electrical and Electronic Engineering |
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School of Electrical and Electronic Engineering Volkau, Ihar Krasovskii, Sergei Mujeeb, Abdul Balinsky, Helen |
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Article |
author |
Volkau, Ihar Krasovskii, Sergei Mujeeb, Abdul Balinsky, Helen |
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Volkau, Ihar |
title |
Computer vision approach in monitoring for illicit and copyrighted objects in digital manufacturing |
title_short |
Computer vision approach in monitoring for illicit and copyrighted objects in digital manufacturing |
title_full |
Computer vision approach in monitoring for illicit and copyrighted objects in digital manufacturing |
title_fullStr |
Computer vision approach in monitoring for illicit and copyrighted objects in digital manufacturing |
title_full_unstemmed |
Computer vision approach in monitoring for illicit and copyrighted objects in digital manufacturing |
title_sort |
computer vision approach in monitoring for illicit and copyrighted objects in digital manufacturing |
publishDate |
2024 |
url |
https://hdl.handle.net/10356/178926 |
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1806059891643645952 |