An efficient two-stage region merging method for interactive image segmentation
An efficient two-stage region merging method for interactive image segmentation
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DOI：
10.1016/j.compeleceng.2015.09.013
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发表时间：
2016-08
期刊：
影响因子：
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通讯作者：
Chongbo Zhou;Dongmei Wu;Wenhua Qin;Chuancai Liu
中科院分区：
文献类型：
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作者：
Chongbo Zhou;Dongmei Wu;Wenhua Qin;Chuancai Liu
交互式图像分割旨在从背景中提取用户指定的区域。本文提出了一种基于两阶段区域合并的高效交互式图像分割方法。首先使用自下而上的方法将图像过度分割为许多超像素。利用颜色直方图来表示每个超像素，并计算 Bhattacharyya 系数来衡量两个相邻超像素的相似度。然后，用户在过度分割的图像上手动标记一些表示所需对象和背景的笔划。利用标记的种子超像素，设计了合并策略来实现自适应区域合并。整个合并过程分为两个阶段，不断重复执行，直到没有新的合并发生。在第一阶段，如果标记的超像素是它们的最近邻居，则一些未标记的超像素被合并到标记的前景或背景超像素中。在第二阶段，如果一个超像素是另一个超像素的最近邻居，则将任意两个未标记的超像素合并在一起。进行了大量的实验来评估所提出方法的性能。结果表明，该方法能够可靠、快速地从背景中提取目标。
Interactive image segmentation aims to extract user-specified regions from the background. In this paper, an efficient two-stage region merging based method is proposed for interactive image segmentation. An image is first over-segmented into many super-pixels using a bottom-up method. The color histogram is exploited to represent each super-pixel, and the Bhattacharyya coefficient is computed to measure the similarity of two adjacent super-pixels. Then some strokes, denoting the desired object and background, are manually labeled by the user on the over-segmented image. With the labeled seed super-pixels, a merging strategy is designed to realize adaptive region merging. The whole merging process is divided into two stages, which are repeatedly executed until no new merging occurs. In the first stage, some unlabelled super-pixels are merged into the labeled foreground or background super-pixels if the labeled ones are their nearest neighbors. In the second stage, any two unlabelled super-pixels are merged together if one super-pixel is the nearest neighbor of the other. Extensive experiments are conducted to evaluate the performance of the proposed method. The results show that the proposed method can extract the object reliably and quickly from the background.