Robust and Fast Decoding of High-Capacity Color QR Codes for Mobile Applications

نویسندگان

  • Zhibo Yang
  • Huanle Xu
  • Jianyuan Deng
  • Chen Change Loy
  • Wing Cheong Lau
چکیده

The use of color in QR codes brings extra data capacity, but also inflicts tremendous challenges on the decoding process due to chromatic distortion—cross-channel color interference and illumination variation. Particularly, we further discover a new type of chromatic distortion in high-density color QR codes—cross-module color interference—caused by the high density which also makes the geometric distortion correction more challenging. To address these problems, we propose two approaches, namely, LSVM-CMI and QDA-CMI, which jointly model these different types of chromatic distortion. Extended from SVM and QDA, respectively, both LSVM-CMI and QDACMI optimize over a particular objective function to learn a color classifier. Furthermore, a robust geometric transformation method is proposed to accurately correct the geometric distortion for high-density color QR codes. We put forth and implement a framework for high-capacity color QR codes equipped with our methods, called HiQ. To evaluate the performance of HiQ, we collect a challenging large-scale color QR code dataset, CUHK-CQRC, which consists of 5390 high-density color QR code samples. The comparison with the baseline method [2] on CUHK-CQRC shows that HiQ at least outperforms [2] by 188% in decoding success rate and 60% in bit error rate. Our implementation of HiQ in iOS and Android also demonstrates the effectiveness of our framework in real-world applications.

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عنوان ژورنال:
  • CoRR

دوره abs/1704.06447  شماره 

صفحات  -

تاریخ انتشار 2017