Research Article
Research on License Plate Recognition Methods Based on YOLOv5s and LPRNet
@INPROCEEDINGS{10.1007/978-3-031-50580-5_25, author={Shijian Hu and Qinjun Zhao and Shuo Li and Tao Shen and Xuebin Li and Rongyao Jing and Kehua Du}, title={Research on License Plate Recognition Methods Based on YOLOv5s and LPRNet}, proceedings={Multimedia Technology and Enhanced Learning. 5th EAI International Conference, ICMTEL 2023, Leicester, UK, April 28-29, 2023, Proceedings, Part IV}, proceedings_a={ICMTEL PART 4}, year={2024}, month={2}, keywords={Deep learning License plate detection License plate recognition YOLOv5s LPRNet}, doi={10.1007/978-3-031-50580-5_25} }- Shijian Hu
Qinjun Zhao
Shuo Li
Tao Shen
Xuebin Li
Rongyao Jing
Kehua Du
Year: 2024
Research on License Plate Recognition Methods Based on YOLOv5s and LPRNet
ICMTEL PART 4
Springer
DOI: 10.1007/978-3-031-50580-5_25
Abstract
License plate recognition technology has been applied more and more widely. To meet the speed and accuracy requirements of license plate recognition methods, this paper proposes a license plate recognition method based on YOLOv5s and LPRNet model. First, the YOLOv5s model was used as the detection module, then the detection results were used as the input of the license plate identification module with the LPRNet model as the main part, and finally, the license plate recognition results were output. The practical consequence shows that compared with the other three models for license plate recognition, the recognition method based on YOLOv5s and LPRNet models proposed in this paper has superiorities in the accuracy and speed of license plate identification and the comprehensive identification rate of the license plate is increased to 93%.
