东北大学学报（自然科学版）

东北大学学报(自然科学版) ›› 2009, Vol. 30 ›› Issue (8): 1087-1090+1110.DOI: -

• 论著 • 上一篇    下一篇

运动车辆阴影的快速检测算法

吴成东;王力;张云洲;刘濛;   

  1. 东北大学信息科学与工程学院;
  • 收稿日期:2013-06-22 修回日期:2013-06-22 出版日期:2009-08-15 发布日期:2013-06-22
  • 通讯作者: Wang, L.
  • 作者简介:-
  • 基金资助:
    国家自然科学基金资助项目(60874103)

A fast shadow detection algorithm for moving vehicles

Wu, Cheng-Dong (1); Wang, Li (1); Zhang, Yun-Zhou (1); Liu, Meng (1)   

  1. (1) School of Information Science and Engineering, Northeastern University, Shenyang 110004, China
  • Received:2013-06-22 Revised:2013-06-22 Online:2009-08-15 Published:2013-06-22
  • Contact: Wang, L.
  • About author:-
  • Supported by:
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摘要： 针对室外交通监控系统遇到的环境光性质变化等问题,提出一种运动车辆阴影快速检测算法.算法首先根据局部阴影模型,利用亮度比判据进行阴影初检测,然后根据动态边缘投影估计得到的车体位置剔除伪阴影,最后根据亮度比统计直方图对亮度比判据阈值进行自适应更新.为验证算法的有效性,分别在不同监控场景、不同日照情况下,对车辆阴影检测进行了实验.实验结果表明:该算法检测速度快,精度高,不受光源性质变化造成的颜色漂移现象的影响,能准确剔除阴影,适合室外环境下的车辆动态检测.

关键词: 交通监控, 车辆, 亮度比, 边缘特征, 阴影检测

Abstract: Investigates the effect of change in ambient light on the outdoor traffic surveillance system, then a fast shadow detection algorithm is proposed for moving vehicles. According to the local shading model, in the algorithm the brightness ratios are used as criteria to detect the shadows preliminarily so as to get rid of the pseudo-shadow pixels by dynamic edge projection to obtain the approximate locations of relevant vehicles and, as a result, the thresholds of the criteria can be updated adaptively in compliance with the statistical histogram of brightness ratios. To verify the effectiveness of the proposed algorithm, some tests were done in situ with different scenes and sunlight conditions. The results showed that the proposed algorithm is fast in detection and accurate in ridding shadow without color drift due to change in ambient light. So, it is suitable for the outdoor vehicle detection system.

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