北京邮电大学学报

  • EI核心期刊

北京邮电大学学报 ›› 2009, Vol. 32 ›› Issue (5): 109-113.doi: 10.13190/jbupt.200905.109.gaojx

• 研究报告 • 上一篇    下一篇

基于光照不变特征的椭球法运动阴影检测

高俊祥;杜海清;刘勇   

  1. (北京邮电大学 信息与通信工程学院, 北京 100876)
  • 收稿日期:2008-12-23 修回日期:2009-05-31 出版日期:2009-10-28 发布日期:2009-10-28
  • 通讯作者: 高俊祥

Moving Shadow Detection by Ellipsoidal Method Using Illumination Invariants

GAO Jun-xiang,DU Hai-qing,LIU Yong   

  1. (School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China)
  • Received:2008-12-23 Revised:2009-05-31 Online:2009-10-28 Published:2009-10-28
  • Contact: GAO Jun-xiang

摘要:

为检测视频监控系统中运动目标的阴影,提出了一种基于光照不变特征c1c2c3的检测算法. 该算法首先根据前景像素和处于相同位置的背景像素的c1c2c3之比定义坐标系,并将阴影检测视为该坐标系内阴影和运动物体的分类问题;然后,采用阴影像素在该坐标系中的分布特性构建1个椭球,并将处在椭球内部的像素判别为阴影像素;最后,根据阴影区域的几何信息进行后处理. 实验表明,该算法能有效地检测不同场景、不同运动物体的阴影,并能适应光照条件的变化.

关键词: 模式识别, 运动阴影检测, 智能视频监控

Abstract:

To detect moving shadow in intelligent video surveillance system, a method using illumination invariants c1c2c3is presented. Firstly, the coordinate
systems are defined on the basis of c1c2c3ratios of foreground and b
ackground pixels at the same position. Secondly, the moving shadow detection can be treated as a classification problem of shadows and moving objects in abovementioned coordinate systems. An ellipsoid is further constructed according to the scattering feature of shadow pixels. All the pixels inside the ellipsoid are extracted as shadows. Finally, the postprocessing is performed by exploiting the geometrical property of shadows. Experiments show that the proposed algorithm is robust and effective in detecting shadows for a variety of scenes and moving objects; moreover, it is suited for varying illumination conditions.

Key words: pattern recognition, moving shadow detection, intelligent video surveillance