An Efficient and Robust ALPR Model Using YOLOv8 and LPRNet

ALPR has many applications in the real world like automatic toll collection, traffic management, and law enforcement. This is generally achieved by two basic steps that are detecting the license plate from the image or video footage and then recognizing the characters on it. In this work, we are going to propose a real-time accurate system using two convolutional neural networks (CNN) that are named YOLOV8 and LPRNet. YOLOV8 is the improved and updated version of YOLO algorithms which has shown improvement in recognition and recall rate and also has better recognition speed compared to other versions with a better accuracy rate.