Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/178926
Title: Computer vision approach in monitoring for illicit and copyrighted objects in digital manufacturing
Authors: Volkau, Ihar
Krasovskii, Sergei
Mujeeb, Abdul
Balinsky, Helen
Keywords: Engineering
Issue Date: 2024
Source: 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
Project: IAF-ICP 
Journal: Computers 
Abstract: 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.
URI: https://hdl.handle.net/10356/178926
ISSN: 2073-431X
DOI: 10.3390/computers13040090
Schools: School of Electrical and Electronic Engineering 
Research Centres: HP–NTU Digital Manufacturing Corporate Lab
Rights: © 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/).
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles

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