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Aesthetic QR Code Authentication Based on Directed Periodic Texture Pattern

  • Li Li
  • Min He
  • Jier Yu
  • Jianfeng LuEmail author
  • Qili Zhou
  • Xiaoqing Feng
  • Chin-Chen Chang
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 895)

Abstract

More and more people use mobile phones to buy goods through scanning the printed aesthetic QR code. QR code has become an important payment tool in today’s business. However, there is an inevitable risk in payment processing. In particular, it is difficult to detect whether an aesthetic QR code has been tampered by the attacker. Therefore, it is extremely important to carry out security certification for aesthetic QR code. We propose an algorithm based on the combination of directional periodic texture pattern and aesthetic QR code. Firstly, the aesthetic QR code is generated based on the Positive Basis Vector Matrix (PBVM), whereas the watermark is encoded into 4-bit Gray code and quantized into angles. Then, a periodic texture pattern is generated using a random matrix, and a directed periodic texture pattern is obtained by rotating the texture pattern according to the quantization angle. Finally, the new texture pattern and the aesthetic QR code are fused to obtain an authentication aesthetic QR code. The experiments verified that the aesthetic QR code can be correctly decoded and the watermark can be properly extracted. By utilizing the locating position patterns of the QR code, the additional watermark reference block is not required, therefore, the capacity of the watermark is enhanced. Moreover, the proposed scheme realizes the anti-counterfeiting authentication of aesthetic QR code, and maintains a better visual quality.

Keywords

Aesthetic QR code Watermark Authentication 

Notes

Acknowledgments

This work was mainly supported by National Natural Science Foundation of China (No. 61370218, No. GG19F020033), Public Welfare Technology and Industry Project of Zhejiang Provincial Science Technology Department (No. 2016C31081, No. LGG18F020013, No. LGG19F020016).

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Li Li
    • 1
  • Min He
    • 1
  • Jier Yu
    • 1
  • Jianfeng Lu
    • 1
    Email author
  • Qili Zhou
    • 1
  • Xiaoqing Feng
    • 2
  • Chin-Chen Chang
    • 3
  1. 1.Hangzhou Dianzi UniversityHangzhouChina
  2. 2.Zhejiang University of Finance and EconomicsHangzhouChina
  3. 3.Feng Chia UniversityTaichungTaiwan

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