Research on Intelligent Recognition System for Traffic Violation

Abstract

This paper focuses on the intelligent recognition system of traffic violation on the basis of analyzing urban complex monitoring environment. For the realization that the system integrates the forensics of violation with license plate recognition in all day time, this paper proposes a set of efficient and robust vehicle detection and tracking algorithms. Vehicle detection was realized by the visual features of the license plate and color characteristic of the taillight to detect edge differential motion between image frames. In vehicle tracking, the extraction of large-scale fast stable points by Lucas-Kanade Pyramid method and predictions for tracking taillight based on Kalman method are proposed to realize long-distance stable tracking vehicles in whole day time. The practical applications show the system has excellent performance.