Smart System for Vechicle Number Plate Recognition Using Convolutional Neural Network(CNN)

In the era of smart cities and advanced transportation systems, the need for efficient and accurate vehicle identification has become paramount. This paper introduces a sophisticated system for vehicle number plate recognition leveraging the capabilities of Convolutional Neural Networks (CNNs). The proposed system aims to enhance security, streamline traffic management, and contribute to the evolution of intelligent transportation infrastructure. Its is also used to check for suspicious vehicles or vehicles that were involved in crime, in that case it is useful for the polices to browse the details of the accused vehicles. Integration of the trained CNN model into a comprehensive system capable of real-time video processing demonstrates the system’s applicability in diverse environments. Deployment considerations span various platforms, from centralized servers to edge devices, ensuring adaptability to different deployment scenarios. The existing systems are based on different methodologies but still, it is a challenging task as some of the factors like high speed of the vehicle, non-uniform vehicle number plate, the language of vehicle number and different lighting conditions can affect a lot in the overall recognition rate. Proposed system, driven by CNN technology, stands as a robust solution for accurate and efficient automated identification.