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.%为在高动态光照和复杂路况环境中实现准确的视频检测与数据采集,构建了一套有效的自适应交通摄像控制系统.首先,针对全天候大场景综合检测需求设计高清交通摄像系统,并通过系统辨识确定了核心摄像参数的控制特性;接着,基于车辆号牌和交通场景特点,提出了以车牌亮度中点值和标线区块中点值作为反馈控制指标的视频质量分析算法;最后,使用自适应控制架构综合底层图像质量反馈信息和高层视觉分析检测结果,实现了光照模式的感知适应和控制状态的自主切换.实验与应用结果表明:该系统控制过程快速稳定,能够自动适应不同光照环境,兼顾高清晰车牌识别和大视野交通监控需求,保持良好的全天成像效果,实现了平均97.0%的车流准确度和96.3%的车牌识别率.
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