节点文献
基于均值漂移聚类的运动目标检测
Moving object detection based on Mean Shift clustering
【摘要】 为了有效减少噪声对运动目标检测的影响,提出了一种利用均值漂移聚类实现运动目标检测的方法。首先运用Mean Shift算法分别对三帧连续图像进行平滑去噪处理,然后对图像进行边缘提取,最后通过三帧差分法对三帧图像进行差分,进而得到运动目标。实验结果表明,该方法可以有效地抑制噪声并提取出运动目标。
【Abstract】 In order to reduce the impact of noise on moving target detection effectively. This paper presents a Mean Shift clustering method to detect the moving target. Firstly, noise in three consecutive frames image is removed by using the Mean Shift algorithm. tThen, image edge extraction is done, and the three-frame-differencing method is used for the three consecutive frames image to get the moving object. Experimental results show that this method can restrain the noise and extract the moving target effectively.
【关键词】 运动目标检测;
均值漂移;
三帧差分;
聚类;
【Key words】 moving object detection; Mean Shift; three-frame-differencing; clustering;
【Key words】 moving object detection; Mean Shift; three-frame-differencing; clustering;
- 【文献出处】 微型机与应用 ,Microcomputer & Its Applications , 编辑部邮箱 ,2011年20期
- 【分类号】TP391.41
- 【下载频次】130