VEHICLE NUMBER PLATE RECOGNITION

In recent years, intelligent transportation systems (ITS) have gained significant traction to enhance road safety and automate traffic management. This paper presents a robust system for vehicle number plate recognition and speed detection using machine learning techniques. The proposed approach integrates image processing with machine learning algorithms to automatically detect and recognize vehicle license plates in real-time. The system captures video frames, isolates the number plate using edge detection and morphological operations, and applies Optical Character Recognition (OCR) powered by deep learning models to extract alphanumeric characters accurately. Additionally, speed detection is achieved through framebased vehicle tracking and time-distance calculations. The system is designed to be scalable, efficient, and suitable for smart surveillance applications such as automated tolling, traffic rule enforcement, and stolen vehicle detection. Experimental results demonstrate a high accuracy in both plate recognition and speed estimation across various lighting and environmental conditions, showcasing the system’s practical viability for intelligent traffic monitoring.