Abstract: The need for automatic vehicle identification has grown rapidly with the increase in traffic density and security concerns. Traditional manual checking methods are time consuming and prone to human error. An effective Automatic Number Plate Recognition (ANPR) system is shown in this study, which uses Tesseract OCR for text recognition and OpenCV for picture pre-processing. The system captures vehicle images in real time, applies grayscale conversion, bilateral filtering, and Canny edge detection to isolate the number plate region, and then uses OCR to extract characters. The recognized number is displayed to the user or stored for monitoring and security purposes. According to experimental results, the suggested system performs well in real time and achieves high accuracy in a variety of illumination scenarios, making it appropriate for uses such as parking management, toll collecting, and security monitoring.

Keywords: Automatic Number Plate Recognition, OCR & OpenCV

| DOI: 10.17148/IARJSET.2025.12590