PERTANIKA JOURNAL OF SCIENCE AND TECHNOLOGY

Vehicle number is an essential issue for intelligent traffic monitoring systems. It plays a significant role in the transportation sector. In addition, recent population growth and human needs have increased due to the use of vehicles. Therefore, controlling traffic is becoming a complex problem to solve. An Automated Plate Number Recognition System (ANPR) program is needed for traffic control. This research includes developing and implementing a multi-stage preprocessing methodology with various techniques to identify vehicles’ plate numbers. The detection system can achieve successful vehicle management: car parking as a case study. The proposed ANPR system employs a template matching algorithm based on a multi-stage preprocessing technique for character identification. Those techniques include noise filtering, component isolation, and correlation-based similarity measurements. The methodology process steps are grayscale conversion, binarisation, bilateral filtering, edge detection, contour localisation, segmentation using connected components, and character recognition through cross-correlation. The system was evaluated on 20 Iraqi one-line plates and achieved a recognition accuracy of 91%.