关键词: 运动目标检测, 混合高斯模型, HSV空间, 阴影抑制

Abstract:

As a classical method in moving target detection, the background subtraction of the Gaussian mixture model has been widely applied in intelligent video surveillance system. However, this classical method easily recognizes shadows as a part of a moving target. So in this paper, we present a moving target detection algorithm combining the Gaussian mixture model and the shadow suppression in HSV space to overcome the shortage in distinguishing shadows from a moving target. First, we use the three frames subtraction method to detect the changed area in the image. Then we transform RGB space into HSV space to detect moving targets preliminarily. Finally, we detect shadows from the moving target through the features that the gray value of shadows is smaller than that of background and the gray value of the foreground is larger than that of the background. Experimental results suggest that the improved algorithm can obviously improve the detection effect by suppressing the interference of shadows of moving targets and also has good realtime performance.

Key words: moving target detection;Gaussian mixture model;HSV space;shadow suppression