Embedded product authentication codes in additive manufactured parts: Imaging and image processing for improved scan ability

被引:13
作者
Chen, Fei [1 ]
Zabalza, Jaime [2 ]
Murray, Paul [2 ]
Marshall, Stephen [2 ]
Yu, Jian [3 ]
Gupta, Nikhil [1 ]
机构
[1] NYU, Composite Mat & Mech Lab, Mech & Aerosp Engn Dept, Tandon Sch Engn, Brooklyn, NY 11201 USA
[2] Univ Strathclyde, Dept Elect & Elect Engn, 204 George St, Glasgow G1 1XW, Lanark, Scotland
[3] US Army, Res Lab, CCRL WMM D, Aberdeen Proving Ground, MD 21005 USA
关键词
Additive manufacturing; 3D printing; Cyber-physical system; Product authentication; Image processing; TOPOLOGY OPTIMIZATION; MECHANICAL-BEHAVIOR; SUPPLY CHAIN; SECURITY; CHALLENGES; MODELS; ATTACK;
D O I
10.1016/j.addma.2020.101319
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The layer-by-layer printing process of additive manufacturing methods provides new opportunities to embed identification codes inside parts during manufacture. These embedded codes can be used for product authentication and identification of counterfeits. The availability of reverse engineering tools has increased the risk of counterfeit part production and new authentication technologies such as the one proposed in this paper are required for many applications including aerospace components and medical implants and devices. The embedded codes are read by imaging techniques such as micro-computed tomography (micro-CT) scanners or radiography. The work presented in this paper is focused on developing methods that can improve the quality of the recovered micro-CT scanned code images such that they can be interpreted by standard code reader technology. Inherent low contrast and the presence of imaging artifacts are the main challenges that need to be addressed. Image processing methods are developed to address these challenges using titanium and aluminum alloy specimens containing embedded quick response (QR) codes. The proposed techniques for recovering the embedded codes are based on a combination of mathematical morphology and an innovative de-noising algorithm based on optimal image filtering techniques. The results show that the proposed methods are successful in making the codes scannable using readily available smartphone apps.
引用
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页数:10
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