Abstract
Color brings extra data capacity for QR codes, but it also brings tremendous challenges to the decoding because of color interference and illumination variation, especially for high-density QR codes. In this paper, we put forth a framework for high-capacity QR codes, HiQ, which optimizes the decoding algorithm for high-density QR codes to achieve robust and fast decoding on mobile devices, and adopts a learning-based approach for color recovery. Moreover, we propose a robust geometric transformation algorithm to correct the geometric distortion. We also provide a challenging color QR code dataset, CUHK-CQRC, which consists of 5390 high-density color QR code samples captured by different smartphones under different lighting conditions. Experimental results show that HiQ outperforms the baseline [1] by 286% in decoding success rate and 60% in bit error rate.
| Original language | English |
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| Title of host publication | 2016 IEEE International Conference on Image Processing, ICIP 2016 - Proceedings |
| Publisher | IEEE Computer Society |
| Pages | 2866-2870 |
| Number of pages | 5 |
| ISBN (Electronic) | 9781467399616 |
| DOIs | |
| Publication status | Published - Aug 3 2016 |
| Externally published | Yes |
| Event | 23rd IEEE International Conference on Image Processing, ICIP 2016 - Phoenix, United States Duration: Sept 25 2016 → Sept 28 2016 |
Publication series
| Name | Proceedings - International Conference on Image Processing, ICIP |
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| Volume | 2016-August |
| ISSN (Print) | 1522-4880 |
Conference
| Conference | 23rd IEEE International Conference on Image Processing, ICIP 2016 |
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| Country/Territory | United States |
| City | Phoenix |
| Period | 9/25/16 → 9/28/16 |
Bibliographical note
Publisher Copyright:© 2016 IEEE.
ASJC Scopus Subject Areas
- Software
- Computer Vision and Pattern Recognition
- Signal Processing
Keywords
- Color interference
- Color recovery
- High capacity
- Illumination variation
- QR code