Abstract :

Vehicle number plate recognition has become a critical technology for traffic monitoring, security, and law enforcement. Automatic Number Plate Recognition (ANPR) systems are widely used to identify vehicles efficiently without human intervention. This project focuses on developing a robust number plate recognition system using image processing techniques. The system captures vehicle images using a camera and preprocesses them for enhanced clarity. Techniques like grayscale conversion, filtering, and edge detection are applied to detect the number plate region. Character segmentation is performed to isolate individual alphanumeric symbols. Optical Character Recognition (OCR) algorithms are used to convert segmented characters into readable text. The system can operate under varying lighting conditions and different plate sizes. Noise reduction and morphological operations are applied to improve detection accuracy. The proposed model is trained to recognize plates with different fonts a