Abstract: Background subtraction is a foreground detection method, and the key step of which is the background modeling. GMM（Gaussian Mixture Model） background modeling method is used most widely. Recently a method called ViBe（Visual Background extractor） has caught more and more attention for its simplicity and high speed. It’s still difficult to detect the foreground for the outdoor video because of the the complex background, such as the shivering or trembling leaves of the trees. Regarding this fact, a morphology post-processing is used to filter the results of ViBe, i.e. with the opening operation to remove the noise, then with the closing operation to fill small voids within the object. The performance is evaluated with ROC curve. The results show that the performance is improved greatly with the morphology post-processing, for outdoor video Watersurface, TPR of the system performance is improved 31% after morphology processing when FPR is 1%.

Key words: foreground detection, ViBe algorithm, morphology post-processing, ROC curve

摘要： 背景差分法是实际中应用最广泛的前景检测方法，其关键是背景建模，比较常用的背景建模方法是高斯混合模型GMM（Gaussian Mixture Model）。最近一种称为视觉背景抽取算法ViBe（Visual Background extractor）由于其简单、快速的特点得到了越来越多的重视。但对于存在动态背景的户外视频，仍然存在噪声及背景的干扰。提出用形态学方法对算法进行改进，即先用开操作来消除噪声，再用闭操作来填充物体内细小空洞等。用ROC曲线测试了算法性能，结果表明，进行形态学处理后算法性能有了比较大的提高，比如对于户外视频Watersurface，在FPR为1%时TPR最高提高了31%。

关键词: 前景检测, ViBe算法, 形态学处理, ROC曲线