基于统计背景模型的运动目标检测方法

运动目标检测是计算机视觉、视频处理等应用领域的重要研究内容。其中减背景技术是一种常用方法。在减背景方法中，背景模型的提取、更新、背景扰动、外界光照条件变化、阴影检测等是必须要考虑的问题。提出了一种有效的运动目标检测方法，较好地解决了以上问题，首先利用统计的方法得到背景模型，并实时地对背景模型更新．以适应光线变化和场景本身的变化，用形态学方法和检测连通域面积进行后处理，消除噪声和背景扰动带来的影响，在HSV色度空间下检测阴影，得到准确的运动目标。实验结果表明，该方法是快速有效的。

Moving Objects Detection Method Based on Statistical Background Model

Moving objects detection is an important research aspect of computer vision and video processing. Background subtraction is a commonly used method. The abstraction and update of background, the effect of background disturb , illumination changes and shadows are the problems that must be considered in background subtraction method. This paper presents an effective moving objects detection method, which solves all the problems presented above effectively. A statistical method is used to obtain the background model ,which is updated real time in order to adapt to illumination changes and scene changes. After threshold operation, morphologic operation and connected region area measurement are introduced to solve background disturb problem. At last, shadow is detected using HSV color space information. Experiment results show that presented method is fast and effective .