LICENSE PLATE DETECTION USING MACHINE LEARNING

Abstract

A crucial technology with many applications in traffic management, security, and law enforcement is license plate detection utilizing machine learning. In this abstract, a machine learning-based method for precisely locating and identifying license plates in pictures and video streams is presented. Data gathering, preprocessing, object detection using deep learning methods like YOLO, license plate recognition using optical character recognition (OCR), and post-processing to improve findings are all part of the mPlate Detection, OpenCV module, OCR Technology.ethodology. Metrics including precision, recall, F1-score, are used to assess performance. The system offers enormous promise for improving efficiency and safety in numerous sectors when it is implemented in real-world circumstances, whether on edge devices or in the cloud. This abstract emphasizes how important machine learning is for automating difficult processes, solving real-world problems, and improving CV. The trained model can also be used in a variety of applications, including security systems, toll booth monitoring, parking enforcement, traffic management systems, and parking enforcement. The system can be implemented on edge devices for real-time processing or in the cloud for scalability depending on the individual requirements of the application.