计算机科学
编码(集合论)
可制造性设计
特征(语言学)
特征提取
移动设备
软件
人工智能
可靠性(半导体)
嵌入式系统
计算机视觉
操作系统
工程类
机械工程
物理
哲学
功率(物理)
集合(抽象数据类型)
量子力学
程序设计语言
语言学
作者
Yulong Yan,Zhuo Zou,Hui Xie,Yu Gao,Lirong Zheng
出处
期刊:IEEE Internet of Things Journal
[Institute of Electrical and Electronics Engineers]
日期:2021-04-15
卷期号:8 (8): 6789-6799
被引量:11
标识
DOI:10.1109/jiot.2020.3035697
摘要
This article presents an Internet-of-Things (IoT) anti-counterfeiting system that uses visual features combined with the quick response (QR) code. The visual features guarantee the authenticity of a product with the QR code for tracking and tracing. Two visual features, i.e., natural texture features and printed micro features are exploited in the proposed system. The natural texture features use the texture of fiber paper to achieve physical unclonable function (PUF), while the micro features are artificially generated for improved industrial manufacturability and reliability. Features are generated and registered in the production phase when the QR code is printed. In the anti-counterfeiting verification phase, the feature obtained through the feature extraction algorithm is compared with the record to calculate similarity, which indicates the verification result. Such an approach is fully compatible with the QR code-based logistic process without any additional manufacturing cost. A user-friendly application has been developed on a mobile platform that facilitates easy-to-use and affordable devices for verification, such as a mobile phone or a handheld code reader. The experimental results show 99.6% and 99.9% accuracy of anti-counterfeiting verification for texture features and micro features, respectively. The system with corresponding algorithms and software has been demonstrated in real-life products.
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