Multi-residual generative adversarial networks for QR code deblurring
Mingyue Wang, Kecheng Chen, Fanqiang Lin · International Conference on Electronic Information Technology (EIT 2022) · 2022
Motion blur and ambient noise are the main reasons that affect quick response (QR) code recognition. In this paper, we propose a novel deep learning approach to deblur the QR codes and realize the effective recognition of deblurring QR codes by using generative adversarial networks (GANs). We estimate the blur kernel and ambient noise of the blur QR code in the dataset using GANs, so as to realize the transformation from the blur QR code image to the sharp image. We also propose an expansion method of QR codes dataset, and achieve better generalization performance of the model. The experimental results show that our approach can effectively estimate the blur kernel and ambient noise that can realize the deblurring of QR code.