The vehicle congestion on the road is increasing day by day and also the management of such large traffic by traditional approach isn’t adequate enough. To eliminate this problem, the project is developed using machine learning in which the testing model is trained to extract the needed image about traffic Information. Extracted information from image sequences of testing model can give us real information to create the database which is the captured images like accident, foggy places, collision of the vehicles, traffic signal, no traffic jam etc. take the image from testing model and processing the trained model which compares the new image and trained image and identify the reason for violation or reason for accident. Data processing will be done to determine the reason under the cause of the accident. This application is utilizing image processing methods designed and modified to the needs and constraints of traffic analysis. Therefore, it shows that it can reduce the traffic congestion and avoids the time being wasted.
TRAFFIC ANALYSIS USING IMAGE PROCESSING