Automated Number Plate Analysis: Using Yolov8 and Easyocr for Enchanted Surveillance

This article presents an ANPR system based on the YOLOv8 deep learning model. The system follows two-stage pipeline: the first stage utilizes YOLOv8 for precise to effectively detect license plates, followed by a second phase where Optical Character Recognition (OCR) is applied to extract the alphanumeric text. The model. is trained on large dataset and generalizes well to various types of plates, vehicles, and harsh environment situations like dynamic lighting. The system is highly accurate in detection and recognition in real-time and can be used in traffic monitoring, tolling, policing, and parking. YOLOv8 has notable speed and accuracy over the past models, and the OCR module has proper character reading. Modularity also facilitates easy integration into bigger intelligent transportation systems (ITS). Overall, the proposed ANPR system is economic, scalable, and feasible for automated vehicle recognition in public and private applications.