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REGION MERGING VIA GRAPH-CUTS

机译:通过图形合并区域

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In this paper, we discuss the use of graph-cuts to merge the regions of the watershed transform optimally. Watershed is a simple, intuitive and efficient way of segmenting an image. Unfortunately it presents a few limitations such as over-segmentation and poor detection of low boundaries. Our segmentation process merges regions of the watershed over-segmentation by minimizing a specific criterion using graph-cuts optimization. Two methods will be introduced in this paper. The first is based on regions histogram and dissimilarity measures between adjacent regions. The second method deals with efficient approximation of minimal surfaces and geodesics. Experimental results show that these techniques can efficiently be used for large images segmentation when a pre-computed low level segmentation is available. We will present these methods in the context of interactive medical image segmentation.
机译:在本文中,我们讨论了使用图割来优化分水岭变换区域的合并。分水岭是一种分割图像的简单,直观和有效的方法。不幸的是,它存在一些局限性,例如过度分割和对低边界的检测不良。我们的分割过程通过使用图切割优化来最小化特定标准,从而合并了分水岭过度分割的区域。本文将介绍两种方法。第一种基于区域直方图和相邻区域之间的相异性度量。第二种方法处理最小曲面和测地线的有效近似。实验结果表明,当可以使用预先计算的低级分割时,这些技术可以有效地用于大图像分割。我们将在交互式医学图像分割的背景下介绍这些方法。

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