AN AI-BASED AUTOMATIC LICENSE PLATE RECOGNITION SYSTEM

Abstract

The rapid progress of Deep Learning has driven advancements in image processing and computer vision, making artificial neural networks the standard tool for these tasks. This paper focuses on explaining neural networks, particularly in object detection models, and aims to build a practical Automatic License Plate Recognition system. The system's development is driven by the technology's wide applicability in various fields and its importance in modern infrastructure like road systems. The study will experiment with building the system and explore potential applications beyond license plate recognition, such as in autonomous driving. The thesis outlines goals including developing accurate algorithms for license plate detection and optical character recognition, integrating them into a real-time system, and evaluating its performance and applications. The ultimate aim is to create a beneficial automatic license plate recognition system that contributes to computer vision and inspires further research in the field.