A General Approach to Robust QR Codes Decoding

With the continued proliferation of smart mobile devices, Quick Response (QR) code has played an important role in daily life. They may be distorted and partially invisible due to bright spots, folding and stains When they are printed on soft materials such as plastic bags. Existing scanners may fail in detecting and decoding QR codes due to distortion. In this paper, we propose a simple but effective approach to decoding distorted and partial QR codes. First, we improve an existing QR code detection algorithm to extract QR codes. Then based on the structural features of QR codes that white and black modules are staggered, we propose a novel distortion correction mechanism that uses an adaptive window to match each module. In order to tackle the problem of invisibility, we print multiple QR codes and capture them in an image. Considering confidence of each module in separate, we reconstruct a relatively complete QR code. Extensive experiments have been conducted to evaluate the performance of our approach. The results show that our approach improves the decoding rate by 50% – 60% compared to the other two baselines.