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The Improvement of the Processes of a Class of Graph-Cut-Based Image Segmentation Algorithms

机译:一类基于图割的图像分割算法过程的改进

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In this paper, an analysis of the basic process of a class of interactive-graph-cut-based image segmentation algorithms indicates that it is unnecessary to construct n-links for all adjacent pixel nodes of an image before calculating the maximum flow and the minimal cuts. There are many pixel nodes for which it is not necessary to construct n-links at all. Based on this, we propose a new algorithm for the dynamic construction of all necessary n-links that connect the pixel nodes explored by the maximum flow algorithm. These n-links are constructed dynamically and without redundancy during the process of calculating the maximum flow. The Berkeley segmentation dataset benchmark is used to prove that this method can reduce the average running time of segmentation algorithms on the premise of correct segmentation results. This improvement can also be applied to any segmentation algorithm based on graph cuts.
机译:本文通过对一类基于交互式图割的图像分割算法的基本过程的分析表明,在计算最大流量和最小流量之前,无需为图像的所有相邻像素节点构造n链接。削减。有许多像素节点根本不需要构造n链接。基于此,我们提出了一种新的算法,用于动态构建所有必要的n链接,这些链接连接最大流量算法探索的像素节点。这些n链接是动态构建的,在计算最大流量的过程中没有冗余。伯克利分割数据集基准测试证明该方法可以在正确分割结果的前提下减少分割算法的平均运行时间。这种改进也可以应用于基于图割的任何分割算法。

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