Detection of Traffic Violation and Vechicle Number Plate Using Computer Vision

A novel approach for detecting numberplate for violation identification is introduced in this research. The main objective of this research is to create the intelligent system for vehicle detection and number plate identification. For the purpose of identifying automobiles that are present inside the video frames, the system makes use of cutting-edge object identification algorithms and SORT (Simple online real-time tracking). When objects are correctly identified, the system is able to study their behaviour and determine whether or not they follow to traffic regulations. During the categorization phase, it is determined whether or not a vehicle has done anything that is against the rules of traffic signals, such as running a red light. For the purpose of training and fine-tuning the deep learning models, the project makes use of a comprehensive dataset consisting of labelled traffic situations. This allows for the research to achieve robust performance. Another thing that we have done is teach a specialized model to recognize red, yellow, and green lights as well as pedestrian crossings.