Robust and Fast Decoding of High-Capacity Color QR Codes for Mobile Applications
| Autor: | Yang, Zhibo, Xu, Huanle, Deng, Jianyuan, Loy, Chen Change, Lau, Wing Cheong |
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| Rok vydání: | 2017 |
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| Druh dokumentu: | Working Paper |
| DOI: | 10.1109/TIP.2018.2855419 |
| Popis: | 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 QDA-CMI optimize over a particular objective function to learn a color classifier. Furthermore, a robust geometric transformation method and several pipeline refinements are proposed to boost the decoding performance for mobile applications. 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. Comment: 15 pages, 10 figures, submitted to IEEE Transaction on Image Processing |
| Databáze: | arXiv |
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