High-Performance Embedded System Design for QR Code Recognition With Deep Learning

Aiming to address the issue that the typical QR code recognition system is sensitive to the influence of factors such as fuzziness and equipment, resulting in decreased recognition performance, we suggest a deep learning algorithm and a Xilinx ZYNQ platform-based QR code recognition system solution in this research. The system created a recognition algorithm based on the YOLO v3 algorithm and an image deblurring algorithm based on the generative adversarial network model framework which effectively removes Gaussian blur from QR code images by adding a relative entropy loss function. Additionally, hardware circuit design and Linux system porting are finished on the ZYNQ side, and then the entire system is installed and tested. The results demonstrate that the system outperforms the Advanced RISC Machine platform of the experimental control, achieving a recognition rate of 85.9% on the complicated environment test set and a recognition speed of 93 ms for a single image.