An AI-Based Traffic Violation Detection System Using Computer Vision

This system presents a Traffic Violation Detection System designed to automatically identify common road rule violations using image and video processing techniques. The system analyses traffic footage to detect vehicles, track their movement, and observe their behavior at key points such as junctions and pedestrian crossings. Based on predefined rules, the system can recognize violations such as signal jumping, wrong-lane driving, over-speeding, and failure to follow road markings. Once a violation is detected, the system captures the relevant evidence frame and extracts the vehicle’s number plate for record-keeping. The collected information is then stored for further review or enforcement actions. The proposed system reduces the need for continuous manual monitoring, provides consistent detection accuracy, and supports improved traffic management and road safety.