Adaptive Imaging Control System Based on Traffic Video Analysis

To ensure accurate video detection and data collection under high dynamic illumination and complicated road conditions, an adaptive traffic imaging control system was developed. A high-definition traffic imaging system was designed to meet the needs of full-time wide-field comprehensive detection. The control characteristics of the imaging parameters were acquired through system identification. Based on license-plate properties and traffic scenes, a video-analysis algorithm computing mid-values of license-plate images and road-marking blocks as feedback control variables, was proposed. In an adaptive control framework combining low-level image-quality feedback and high-level visual-detection results, autonomous illumination-mode adaption and control-state switching were realized. The experimental and application results show that the system control process is fast and stable. It can adapt to different illumination conditions, balance the requirements of high-definition license-plate recognition and wide-field traffic surveillance, maintain good all-day imaging effects, and achieve 97.0% traffic-flow accuracy and a 96.3% license-plate recognition rate.