Li Hongyu, Chen Wenbin, Shen I-Fan
Department of Computer Science and Engineering, Fudan University, Shanghai, China.
IEEE Trans Vis Comput Graph. 2006 May-Jun;12(3):289-300. doi: 10.1109/TVCG.2006.54.
In this paper, we propose an approach for 2D discrete vector field segmentation based on the Green function and normalized cut. The method is inspired by discrete Hodge Decomposition such that a discrete vector field can be broken down into three simpler components, namely, curl-free, divergence-free, and harmonic components. We show that the Green Function Method (GFM) can be used to approximate the curl-free and the divergence-free components to achieve our goal of the vector field segmentation. The final segmentation curves that represent the boundaries of the influence region of singularities are obtained from the optimal vector field segmentations. These curves are composed of piecewise smooth contours or streamlines. Our method is applicable to both linear and nonlinear discrete vector fields. Experiments show that the segmentations obtained using our approach essentially agree with human perceptual judgement.
在本文中,我们提出了一种基于格林函数和归一化切割的二维离散向量场分割方法。该方法受离散霍奇分解的启发,使得离散向量场可以分解为三个更简单的分量,即无旋、无散和调和分量。我们表明,格林函数法(GFM)可用于近似无旋和无散分量,以实现向量场分割的目标。表示奇点影响区域边界的最终分割曲线是从最优向量场分割中获得的。这些曲线由分段光滑的轮廓或流线组成。我们的方法适用于线性和非线性离散向量场。实验表明,使用我们的方法获得的分割结果与人类的感知判断基本一致。