针对固定摄像机监控中多运动目标自动分割问题，本文提出了一种基于背景差分和水平集的新方法。首先，该方法通过求解连续三帧图像的对称差分，确定出当前帧中的背景像素点，并对背景像素点的灰度值进行统计，最后选择频率最高的灰度值作为该点背景像素灰度值来重构背景。其次，提出了基于8-邻域搜索的区域生长算法完成连通区域的检测，并通过设置阈值和连通域分析，消除背景块噪声并标定出运动目标区域。最后，对所有运动目标区域块，分别采用无需重新初始化的水平集算法作分割，得到封闭和完整的目标轮廓。实验结果表明，该算法能实现固定摄像机监控中刚体或非刚体的多运动目标的自动检测和轮廓分割。

Based on background difference and level set, a novel segmentation method was presented for multiple moving targets in static camera surveillance. Firstly, background pixels in current frame were obtained by calculating symmetric difference of three consecutive frames, and the gray value of every background pixel was recorded. Then the gray value with the biggest frequency was selected for each pixel to reconstruct whole background. Secondly, the region growth algorithm based on the 8-neighbour search was proposed to detect connected regions, and small background noise regions were removed by setting a threshold. Then by analyzing connected regions, moving target regions were marked. Finally, the level set algorithm without re-initialization was adopted to segment each target region. The closed and entire target contour was gotten. Experiments show that this approach can realize automatic detection and contour segmentation of rigid or non-rigid moving targets in static camera surveillance.