针对具有复杂背景的视频序列中运动物体的分割问题,在利用Canny算法将空间边缘信息结合到基于变化的分割技术的基础上,提出在预处理阶段对视频序列的灰度图进行局部对比度增强处理,以增加前景物体与背景对比度的观点,首先解决了许多视频分割算法都存在的对比度较低带来的分割困难问题,同时通过设计3×3模板的滤波器来滤除对比度增强之后引入的少量噪声;然后针对复杂背景的情况,设计了一种视频对象自动分割新算法,该算法利用随机信号的统计特性累计得到算法所需的背景来实现背景信息的自动获取;最后利用背景累积过程中分类讨论的观点,解决了物体停止运动时间较长时造成分割丢失的问题。实验结果表明,该算法可以有效地将运动物体从视频序列中自动地分割出来。

On the base of combining change-detection-based segmentation approach and spatial edge information by canny edge detection,an algorithm is proposed in which local contrast enhancement is applied to improve the contrast between foreground object and background in the pre-processing stage,and the problem caused by low contrast is solved.A filter was designed to remove a small quantity of noise caused by contrast enhancement;Then for the complex background,the algorithm utilizes probability-based classification to accumulate the background information,which it is needed by the original segmentation algorithm,and consequently realizes the capturing of background information automatically; Finally,the paper proposed that three situation should be discussed in the process of accumulating background information.The proposed algorithm is evaluated on several MPEG- 4 test sequences and produces promising results.