Graph based segmentation with minimal user interaction

Huaizhong Zhang, Ehab Essa, Xianghua Xie
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引用次数: 4

Abstract

In this paper, we present a graph based segmentation method that only requires a single point from user initialization. We incorporate a new image feature into the segmentation scheme. It is derived from a vector field that takes into account gradient vector interactions across the image domain, and has the simplicity of edge based features but also proves to be a useful region indication in two-level segmentation. Effective vector field diffusion is proposed to deal with excessive image noise. Based on a single user point we unravel the image and transfer the object segmentation into a height field segmentation in polar coordinates, which in effect imposes a star shape prior. The search of a minimum closed set on a node weighted, directed graph produces the segmentation result. Comparative analysis on real world images demonstrates promising performances of the proposed method in segmentation accuracy and its simplicity in user interaction.
基于图形的分割与最小的用户交互
在本文中,我们提出了一种基于图的分割方法,它只需要用户初始化的一个点。我们在分割方案中加入了一个新的图像特征。它由一个考虑了图像域上梯度向量相互作用的向量场推导而来,具有基于边缘特征的简单性,但也被证明是两级分割中有用的区域指示。针对图像噪声过大的问题,提出了有效矢量场扩散的方法。基于单个用户点,我们将图像展开,并将目标分割转换为极坐标系下的高度场分割,这实际上施加了一个星形先验。在一个节点加权有向图上搜索最小闭集产生分割结果。对真实图像的对比分析表明,该方法在分割精度和用户交互简单性方面具有良好的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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