Traffic Rules Violation Detection System
Dnyanendra Jagadish Borase · International Journal for Research in Applied Science and Engineering Technology · 2023
Abstract: The paper presents a system that uses surveillance videos to automatically detect bike riders without helmets by us-ing object segmentation and background subtraction techniques. A consolidation approach is introduced to improve accuracy, and three feature representations are compared. The system achieves a detection accuracy of 93.80 percentage and has an average processing time of 11.58 milliseconds, making it a cost-effective and real-time solution for managing traffic violations related to helmet usage