Paper Key : IRJ************261
Author: Nitish Naik,Akash Shahane,Tanmay Tharkude,Tushar Pathak,Jadhav Ganesh D
Date Published: 14 Nov 2024
Abstract
With the countrys rapid economic growth, the increasing number of vehicles on the road has led to escalating traffic-related issues, including accidents and frequent violations of traffic laws. Efficient traffic management has become essential to mitigate these issues and enhance road safety.Intelligent systems, such as those using Convolutional Neural Networks (CNNs), offer promising solutions for traffic monitoring and management. Among these, a license plate detection and recognition system has emerged as a viable approach, capable of automatically identifying vehicles and tracking law enforcement more effectively.This system is designed with two core modules: license plate detection and character recognition. Real-time images of vehicles are captured through digital cameras, which are then processed digitally to isolate and distinguish the license plate region. Advanced techniques are applied to enhance the quality of the extracted license plate image, improving the systems accuracy. For segmentation and recognition, CNNs play a crucial role, where individual characters on the license plate are enclosed in bounding boxes, and each character is classified using a CNN-based approach.By integrating CNNs for both segmentation and character recognition, this license plate recognition system provides an efficient and accurate solution to support traffic management and law enforcement efforts. This intelligent approach has the potential to improve safety, reduce traffic violations, and streamline vehicle monitoring, contributing to more organized and safer roadways.
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