Performance Analysis of License Plate Detection and Recognition Using YOLO and OCR

For applications like automated toll collection and traffic monitoring, license plate recognition, or LPR, is essential. In order to enhance license plate identification and recognition performance, this study provides a method that combines the You Only Look Once (YOLO) object detection algorithm with optical character recognition (OCR). In complicated surroundings, YOLO provides high-accuracy real-time detection, while OCR efficiently recognises alphanumeric characters. We assessed the system's performance by examining processing time, accuracy of detection and recognition, and a publically accessible dataset. The combined strategy greatly outperforms standard methods, according to the results. The system exhibits resilience in the face of obstacles like dim lighting and partial occlusions. An dependable LPR solution for intelligent transportation systems is provided by this combination.