Intelligent system architecture for a vision-based contactless apprehension of traffic violations

Abstract

The paper presents an intelligent system architecture for detecting traffic violations based on vision. This study aims to better manage traffic conditions in block intersections by employing a computer vision system that facilitates the identification of traffic violations committed in the road intersection. The architecture includes three sub-system: video capture sub-system, intelligent operating architecture (IOA) sub-system, and output sub-system. The IOA manages different algorithms to recognize traffic violations. The algorithms developed are vehicle detection and tracking, plate number localization, plate character recognition, and traffic violations identification. The traffic violations addressed in this study are number coding, over-speeding, and swerving. The research study is in the initial phase of development, and the experiment results showed that optical character recognition have 86.11% accuracy and speed measurement have 88.45% accuracy.