摘要
在户外的视频监控系统中,运动目标的阴影降低了系统对目标识别与跟踪的能力。传统的基于像素的阴影检测算法易受噪声的影响。为了提高阴影检测算法的准确性,提出了一种基于区域与光照不变性的运动阴影检测算法。该算法从阴影的物理特性出发,考虑了区域内像素的总体特征。将运动区域采用EM聚类算法进行分块,对其中的小块向邻近的大块进行合并。对其中的每一块,根据阴影区域和相对应的背景区域之间的光照不变性进行阴影检测。实验结果表明,该算法能够很好地抑制噪声,准确地检测出阴影,明显比基于像素的算法有效。
Cast shadows from moving objects reduce the general ability of robust classification and tracking of these objects, in outdoor surveillance applications. Classic pixel-based object shadow detection algorithm limits the performance, owing to noise. An algorithm for segmentation of cast shadows was proposed with improved accuracy, combining region with illumination invariant. This algorithm takes into account the features of all the pixels in a region. Using Expectation- Maximization （EM） cluster, the moving region was segmented into blocks with the smaller blocks combined with the neighbor bigger blocks. Shadow detection was performed in every block based on the illumination invariant between the shadow region and the corresponding background region. Experimental results show that the proposed algorithm is robust to noise, can detect accurately shadows and is more efficient than the algorithm based on pixel.
出处
《计算机应用》
CSCD
北大核心
2007年第9期2152-2153,2166,共3页
journal of Computer Applications
关键词
阴影检测
光照不变性
EM聚类
目标分割
shadow detection
illumination invariant
EM cluster
object segmentation
