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Seeded Region Merging Based on Gradient Vector Flow for Image Segmentation

机译:基于梯度矢量流的种子区域合并算法

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摘要

Human interaction is a crucial restriction of active contour model, or snakes. In this paper we propose a fully automatic algorithm based on gradient vector flow (GVF) field and watershed-based region merging. Firstly a scalar force field is constructed by minimizing an energy function from the GVF force field. From the scalar field we extract a set of seed points facilely, and get an initial segmentation without doing curve evolution. Then a Region Adjacency Graph (RAG) based region merging algorithm is applied to get the final result. Several experimental results demonstrate that this method is efficient to multiple objects segmentation, and insensitive to noises.
机译:人机交互是主动轮廓模型或蛇的关键限制。在本文中,我们提出了一种基于梯度矢量流(GVF)场和基于分水岭的区域合并的全自动算法。首先,通过最小化来自GVF力场的能量函数来构造标量力场。从标量场中,我们可以轻松地提取一组种子点,并且无需进行曲线演化就可以进行初始分割。然后应用基于区域邻接图(RAG)的区域合并算法来获得最终结果。多个实验结果表明,该方法对多目标分割是有效的,并且对噪声不敏感。

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