A Texture-Hidden Anti-Counterfeiting QR Code and Authentication Method

Author:

Wang Tianyu,Zheng Hong,You ChanghuiORCID,Ju Jianping

Abstract

This paper designs a texture-hidden QR code to prevent the illegal copying of a QR code due to its lack of anti-counterfeiting ability. Combining random texture patterns and a refined QR code, the code is not only capable of regular coding but also has a strong anti-copying capability. Based on the proposed code, a quality assessment algorithm (MAF) and a dual feature detection algorithm (DFDA) are also proposed. The MAF is compared with several current algorithms without reference and achieves a 95% and 96% accuracy for blur type and blur degree, respectively. The DFDA is compared with various texture and corner methods and achieves an accuracy, precision, and recall of up to 100%, and also performs well on attacked datasets with reduction and cut. Experiments on self-built datasets show that the code designed in this paper has excellent feasibility and anti-counterfeiting performance.

Funder

National Key Research and Development Program of China

Hubei Provincial Natural Science Foundation of China

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry

Cited by 7 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. QR Codes: From a Survey of the State of the Art to Executable eQR Codes for the Internet of Things;IEEE Internet of Things Journal;2024-07-01

2. Anti-Counterfeiting Identification WeChat Mini Program Based on Microservices;Computer Science and Application;2024

3. Enhancing Malicious QR Code Link Detection with Swarm-Intelligent Squirrel-Search Optimized ANN;2023 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES);2023-12-14

4. Research on NFC Anti-Counterfeit Traceability Based on Signcryption AlgorithmResearch on NFC Anti-Counterfeit Traceability;2023 4th International Conference on Machine Learning and Computer Application;2023-10-27

5. Anti-counterfeiting textured pattern;The Visual Computer;2023-07-01

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