School of Electronic Information, Wuhan University, Wuhan 430072, China.
School of Cyber Science and Engineering, Wuhan University, Wuhan 430072, China.
Sensors (Basel). 2023 Jan 10;23(2):795. doi: 10.3390/s23020795.
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.
本文设计了一种纹理隐藏 QR 码，以防止由于其防伪能力不足而导致的 QR 码非法复制。通过将随机纹理图案与精化 QR 码相结合，该编码不仅能够进行常规编码，而且具有很强的抗复制能力。基于提出的代码，还提出了一种质量评估算法（MAF）和一种双特征检测算法（DFDA）。MAF 与几种当前无参考的算法进行了比较，在模糊类型和模糊程度上的准确率分别达到了 95%和 96%。DFDA 与各种纹理和角点方法进行了比较，准确率、精度和召回率高达 100%，在减少和裁剪的攻击数据集上也表现良好。在自建数据集上的实验表明，本文设计的代码具有出色的可行性和防伪性能。
