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An IoT-Based Anti-Counterfeiting System Using Visual Features on QR Code
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DOI：10.1109/JIOT.2020.3035697.png)
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Abstract
En 中文
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.
Keywords:
Feature extraction
Visualization
Internet of Things
Feature detection
Printing
Mobile handsets
Physical unclonable function
Anti-counterfeiting
feature extraction
Internet of Things (IoT)
quick response (QR) code
visual feature
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