Paper Contents
Abstract
Automatic Number Plate Recognition (ANPR) is an advanced technology that uses imaging equipment to identify and extract license plate information from drivers. It has become an indispensable tool in applications such as traffic monitoring, toll collection, parking management, and policing. The system usually consists of several stages, such as image capture, preprocessing, location authorization, character classification, and optical character recognition (OCR). Recent advances in machine learning and computer vision have increased the accuracy and performance of ANPR systems, even in low-light, traffic congestion, or similar challenging conditions. License is not a model. This article examines the basic principles and techniques of ANPR systems, highlights their performance, and discusses challenges and future developments in the field.
Copyright
Copyright © 2025 Archita Sharma. This is an open access article distributed under the Creative Commons Attribution License.
