CNN based System for Automatic Number Plate Recognition

Abstract

This study presents a comprehensive approach to Automated Vehicle Number Plate Detection and Recognition, employing image processing and Convolutional Neural Networks (CNNs). The system encompasses two main stages: number plate detection and recognition. Utilizing a digital camera, the system employs image processing to segment the number plate region accurately. A super-resolution method is then applied via CNNs to enhance the image quality. Subsequently, a bounding box method isolates individual characters for precise recognition. In the recognition phase, CNNs extract features for effective classification. The study aims to advance automated vehicle identification systems for law enforcement and parking management applications, promising accurate and efficient number plate detection and recognition. The proposed work has also developed a user interface to ensure the successfulness of the objectives aimed.