• Ms. RUBINA BEGUM

Automatic Number Plate Recognition (ANPR) is a key technology in intelligent transportation systems (ITS), enabling real-time vehicle identification for applications such as traffic management, law enforcement, and toll collection. Traditional methods rely on image processing techniques like edge detection and optical character recognition (OCR), but they are often sensitive to lighting conditions, angle variations, and occlusions. This paper presents an improved ANPR system that integrates machine learning and deep learning approaches to enhance recognition accuracy. By leveraging Convolutional Neural Networks (CNNs) for character recognition and adaptive preprocessing techniques, our system demonstrates robust performance across diverse environmental conditions. Experimental results validate the efficiency of the proposed approach, making it a reliable tool for smart traffic management and security applications.

ANPR, CNN, YOLO

"INTELLIGENT VEHICLE NUMBER PLATE RECOGNITION FOR SMART TRAFFIC MONITORING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 2, page no.445-447, February-2018, Available :http://www.jetir.org/papers/JETIR1802362.pdf

"INTELLIGENT VEHICLE NUMBER PLATE RECOGNITION FOR SMART TRAFFIC MONITORING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 2, page no. pp445-447, February-2018, Available at : http://www.jetir.org/papers/JETIR1802362.pdf