A Comprehensive Review on Car Number Plate Recognition using Image Processing

Abstract: The rapid growth of vehicle populations has made traffic control, law enforcement, and vehicle identification increasingly challenging. Manual methods for recognizing number plates are often slow, inaccurate, and inefficient in busy areas. This study introduces an automated car number plate recognition system that applies image processing and artificial intelligence techniques to detect and interpret vehicle registration details automatically. The proposed framework captures images or video frames of vehicles, enhances them to minimize noise, and isolates the license plate region using advanced detection algorithms. The alphanumeric information on the plate is then extracted and recognized through Optical Character Recognition (OCR). The processed data can be used for diverse applications, including smart traffic monitoring, toll automation, parking management, and security surveillance. Designed for real-time performance, the system demonstrates strong adaptability to varying lighting and environmental conditions while maintaining high accuracy. By automating the identification process, it minimizes human involvement and improves the efficiency and reliability of traffic management systems.