VEHICLE NUMBER PLATE AND SPEED DETECTION USING IMAGE PROCESSING IN MATLAB

The rapid increase in the number of vehicles on roads has led to significant challenges in traffic management, vehicle monitoring, and road safety. Conventional monitoring systems rely heavily on manual effort and costly infrastructure, making them inefficient for large-scale deployment. To address these limitations, this paper presents an automated system for vehicle number plate detection and speed estimation using image processing techniques in MATLAB. The proposed system processes input in the form of images or traffic surveillance videos. Initially, video frames are extracted and preprocessed using grayscale conversion, noise reduction, and contrast enhancement to improve image quality. Edge detection techniques, such as Sobel and Canny operators, are employed to identify potential number plate regions. Subsequently, morphological operations are applied to accurately localize and extract the license plate from the image. Following plate extraction, character segmentation is performed to isolate individual alphanumeric characters. These characters are then recognized using Optical Character Recognition (OCR) techniques, converting them into machine-readable text. In addition to number plate recognition, the system estimates vehicle speed by analysing the displacement of vehicles across consecutive frames in the video sequence. The proposed method offers an efficient, cost-effective, and automated solution for real-time vehicle identification and speed monitoring. It can be applied in various domains, including traffic law enforcement, automated toll collection, parking management, border surveillance, and intelligent transportation systems, thereby enhancing traffic efficiency and road safety