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Improved color image segmentation algorithm based on GrabCut

机译:基于Grabcut的改进的彩色图像分割算法

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In realistic image processing, it is a problem of image foreground extraction. For a large number of color image processing, an important requirement is the automation of the extraction process. In this paper, by automatically setting foreground seed, we improve the image existing segmentation algorithm; by automatically searching image segmentation region, we accomplish image segmentation with the GrabCut algorithm, which is based on Gaussian Mixture Model and boundary computing. The improved algorithm in this paper can achieve the automation of image segmentation, without user participation in the implementation process, at the same time, it improves the efficiency of image segmentation, and gets a good result of image segmentation in complex background.
机译:在现实的图像处理中,它是图像前景提取的问题。对于大量彩色图像处理,重要要求是提取过程的自动化。在本文中,通过自动设置前台种子,我们改进了图像现有分割算法;通过自动搜索图像分割区域,我们使用基于高斯混合模型和边界计算的Grabcut算法来完成图像分割。本文的改进算法可以实现图像分割的自动化,而无需用户参与实现过程,同时提高了图像分割的效率,并在复杂背景中获得了图像分割的良好结果。

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