DefinePK

Abstract

Since the 19th century, the number of vehicles has been increasing rapidly with the growth of the human population. To supervise vehicles, license plates are used all over the world. The license plate is the unique identity for vehicles; that’s why it is always used to monitor and keep records of vehicles by law enforcement, border monitoring, parking control, and many other applications. Monitoring a huge number of vehicles is a difficult task using traditional (manual) methods. The Intelligent License Plate Recognition (ILPR) system overcomes these problems by recognizing plate identities without human involvement through artificial intelligence and machine learning processes. This system extracts the identity number allocated to each vehicle from the license plate and can provide information about a specific vehicle. It can be further applied in regulated zones such as military areas, parking control, toll collection, and for identifying non-tax-paid vehicles. For developing the ILPR system, text extraction and deep learning techniques must be combined.
The ILPR system, developed by integrating Deep Learning (DL), Image Processing (IP), and image-to-text extraction approaches, is used to detect plate identity. YOLOv8 is used for object detection and the OCR engine for text extraction. The system will be capable of detecting live license plates with high accuracy, which will help in regulated zones and traffic system applications.