Advanced Techniques for Improved Bangladeshi Number Plate Detection and Character Recognition in Automated Parking Systems

Abstract

This paper presents a novel technique for efficient extraction of vehicle number plates from camera-captured images and accurate recognition of Bangla characters embedded within them. With the exponential growth of vehicular traffic in densely populated regions like Bangladesh, automation becomes crucial, making vehicle plate recognition pivotal for tracking stolen vehicles and enhancing traffic control measures. Leveraging conventional computer vision and image processing techniques, our proposed system incorporates specific features inherent to Bangladeshi number plates, thus enhancing recognition accuracy. Our application makes use of the OpenCV library to underscore the strength of the algorithm, which has been confirmed through real-time testing across different weather conditions and varying image qualities. The results show a remarkable accuracy rate of 92.3%, affirming our technique's reliability in vehicle number plate detection and character recognition. Moreover, the integration with MySQL database and Arduino UNO enables real-time application in automated parking systems, offering seamless entry procedures and accurate billing, thus addressing critical concerns in modern transportation management systems. Our algorithm not only enhances security measures but also streamlines parking facility management, contributing to safer and more efficient urban mobility solutions.