The Enhancement of Graphic QR Code Recognition using Convolutional Neural Networks

Jong Kai Lee, Yu Mei Wang, Chun Shien Lu, Hsi Chun Wang, Tzren Ru Chou

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The use of QR Code has been flourishing on mobile and tablet platforms. By scanning the code, we can obtain targeted information synchronously. The regular QR Code, which consists of black and white modules, is neither visually pleasing nor recognizable by human vision. The application of graphic QR Code to product packaging and promotion campaign in the market has skyrocketed nowadays. However, printed graphic QR Code accompanies noise phenomenon that interferes the recognition itself and causes failure when user scanning. Therefore, we produce graphic QR Codes by data hiding with error diffusion techniques that first become training data. Then, we apply convolution neural networks to improve the data point recognition of graphic QR Codes. The experimental results show the superiority of the performance in both accuracy and recognition ability in comparison with normal QR Code readers.

Original languageEnglish
Title of host publicationProceedings of the 2019 8th International Conference on Innovation, Communication and Engineering, ICICE 2019
EditorsShoou-Jinn Chang, Sheng-Joue Young, Artde Donald Kin-Tak Lam, Liang-Wen Ji, Hao-Ying Lu, Stephen D. Prior
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages94-97
Number of pages4
ISBN (Electronic)9781728158396
DOIs
Publication statusPublished - 2019 Oct
Event8th International Conference on Innovation, Communication and Engineering, ICICE 2019 - Zhengzhou, Henan Province, China
Duration: 2019 Oct 252019 Oct 30

Publication series

NameProceedings of the 2019 8th International Conference on Innovation, Communication and Engineering, ICICE 2019

Conference

Conference8th International Conference on Innovation, Communication and Engineering, ICICE 2019
CountryChina
CityZhengzhou, Henan Province
Period2019/10/252019/10/30

Keywords

  • convolution neural networks
  • graphic QR Code
  • noise

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Safety, Risk, Reliability and Quality
  • Modelling and Simulation
  • Computer Networks and Communications
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Information Systems and Management

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