Each character of the number plate is segmented using a bounding box method. The super resolution technique is used with the convolutional layer of CNN to reconstruct the pixel quality of the input image. After extracting the number plate region, a super resolution method is applied to convert the low-resolution image into a high-resolution image. Then the system segments the number plate region from the image frame. In the detection part, a vehicle’s image is captured through a digital camera. This system comprises of two parts: number plate detection and number plate recognition. In this research work, a system is developed for detecting and recognizing of vehicle number plates using a convolutional neural network (CNN), a deep learning technique. The intelligent system can play a vital role in traffic control through the number plate detection of the vehicles. In order to overcome these problems, an intelligent traffic monitoring system is required. The significant use of vehicles has increased the probability of traffic rules violation, causing unexpected accidents, and triggering traffic crimes. Vehicles on the road are rising in extensive numbers, particularly in proportion to the industrial revolution and growing economy.
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