An Automatic Framework for Number Plate Detection using OCR and Deep Learning Approach

—The use of automatic number plate detection devices in safety, commercial, and security has increased over the past few years. Number plate detection using computer vision is used to provide fast and accurate detection and recognition. Lately, many computerized approaches have been developed for the identification of vehicle registration details based on license plate numbers using either Deep Learning (DL) methodologies. In the proposed framework, we used Optical Character Recognition (OCR) and a deep learning-based new approach for automatic number plate detection and recognition. A deep learning approach trains the model to recognize the vehicle. The vehicle registration plate area is cropped adequately from the image, and a Convolution Neural Network (CNN) uses OCR to identify numbers and letters. The Jetson TX2 NVIDIA target served as the model's training data source, and its performance has been tested on a public dataset from Kaggle database. We obtained the highest accuracy of 96.23%. The proposed system could recognize vehicle license plate numbers on real-world images. The system can be implemented at security checkpoint entrances in highly restricted areas such as military areas or areas surrounding high-level government agencies.