1. A Texture-Hidden Anti-Counterfeiting QR Code and Authentication Method
- Author
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Tianyu Wang, Hong Zheng, Changhui You, and Jianping Ju
- Subjects
anti-counterfeiting QR code ,Gaussian distribution ,refined QR code ,decoding ,fourier domain ,Chemical technology ,TP1-1185 - 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.
- Published
- 2023
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