Implementation of License Plate Detection Based on Improved YOLOv5s

In order to solve the problem of low accuracy of license plate detection, an improved license plate detection algorithm is proposed. The super-resolution reconstruction network SRGAN is used to enhance the image of the dataset and make the image of the license plate area clearer; The fourth C3 module of YOLOv5s backbone network is replaced with CBAM attention mechanism module to enhance the ability of backbone network to extract feature information, thus improving the detection accuracy. The experimental results show that YOLOv5s network using SRGAN for image enhancement and embedding CBAM attention mechanism improves the accuracy of license plate image.