摘要
复杂场景下的运动目标分割技术是近年来多媒体通信技术研究的热点之一。文中提出一种基于时空马尔可夫随机场模型的运动目标分割技术。首先建立运动序列图像的时空马尔可夫随机场模型并且构造其相应的能量耗费函数 ,通过模型可以提出期望的空间属性。然后利用迭代条件模型 (ICM)算法实现最大后验概率 (MAP)估算问题。最后利用形态滤波的方法对分割结果进行修正。模拟实验结果证明 ,该方法能够有效地抑制图像的噪声 ,对于运动目标的提取有较好的分割效果。
Moving object segmentation technology in complex background is one of the hot point in multimedia communication recently In this paper,a method for moving object segmentation based on Markov random field model is proposed. The Markov random field model based on spatial temporal neighborhood system is given and the cost function is decided by the model Then the maximum posteriori estimator is determined by using the iterated conditional mode algorithms A morphology filter is adopted to get the better result The simulation results show that by the proposed method noise can be reduced and good segmentation results can be obtained
出处
《通信学报》
EI
CSCD
北大核心
2000年第11期63-68,共6页
Journal on Communications
