ABSTRACT:
Colour brings extra data capacity with regards to QR codes, however, it likewise conveys tremendous challenges to the decoding because of color interface and illumination variation, particularly for high-density QR codes. In this project, we put forth a system for high-capacity QR codes, HiQ, which optimizes the decoding algorithm for high-density QR codes to accomplish robust and quick decoding on cell phones, and receives a learning-based approach for color recovery. In addition, we propose a robust geometric transformation algorithm to adjust the geometric distortion. We likewise give a challenging color QR code dataset, CUHK-CQRC, which comprises of 5390 high-density color QR code tests caught by various cell phones under various lighting conditions. Experimental results demonstrate that HiQ out performance the benchmark by in decoding success rate and in bit error rate.
