Abstract:
The implementation of number plate recognition systems has significantly improved the city's traffic conditions. These systems provide guidance for creating an efficient intelligent transportation system. With the rapid growth in vehicle numbers, Automatic Number Plate Recognition (ANPR) has become a crucial tool for traffic management. ANPR plays a vital role in traffic and security surveillance, utilizing advanced technology and image processing techniques to automatically identify characters on vehicle license plates.
In recent years, there have been notable advancements in license plate recognition technology. By employing techniques like Optical Character Recognition (OCR), traffic surveillance can effectively address issues related to criminal investigations, toll collection, traffic monitoring, speed control, and parking management. ANPR systems are indispensable for efficient traffic management and large-scale monitoring in the transportation sector.
Using image processing algorithms and vehicle image datasets, traffic can now be monitored on a massive scale. Processes such as image segmentation, feature extraction, and character recognition allow license plate characters to be identified accurately. The data collected from these systems can be used for a variety of purposes, including commercial applications, traffic management, and law enforcement. The software analyzes vehicle images as input and produces the license plate numbers as output.
Advances in image processing technology have made these systems reliable for detecting traffic and accurately recognizing license plates. Many ANPR systems are now designed with a focus on license plate character recognition, leveraging image processing techniques to enhance their functionality.
