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首页> 外文会议>Conference on Image Processing: Algorithms and Systems III; 20040119-20040121; San Jose,CA; US >Automatic Image Segmentation by Wave Propagation
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Automatic Image Segmentation by Wave Propagation

机译：通过波传播自动分割图像

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摘要

We develop a level set based region growing method for automatic partitioning of color images into segments. Previous attempts at image segmentation either suffer from requiring a priori information to initialize regions, being computationally complex, or fail to establish the color consistency and spatial connectivity at the same time. Here, we represent the segmentation problem as monotonic wave propagation in an absorbing medium with varying front speeds. We iteratively emit waves from the selected base points. At a base point, the local variance of the data reaches a minimum, which indicates the base point is a suitable representative of its local neighborhood. We determine local variance by applying a hierarchical gradient operator. The speed of the wave is determined by the color similarity of the point on the front to the current coverage of the wave, and by edge information. Thus, the wave advances in an anisotropic spatial-color space. The absorbing function acts as a stopping criterion of the wave front. We take advantage of fast marching methods to solve the Eikonal equation for finding the travel times of the waves. Our method is superior to the linkage-based region growing techniques since it prevents leakage and imposes compactness on the region without over-smoothing its boundary. Furthermore, we can deal with sharp corners and changes in topology. The automatic segmentation method is Eulerian, thus it is computationally efficient. We compare our results with a non-Eulerian approach that evaluates the arrival times of multiple waves as well. Our experiments illustrate the robustness, accuracy, and effectiveness of the proposed method.
机译：我们开发了一种基于水平集的区域增长方法，用于将彩色图像自动划分为片段。先前的图像分割尝试要么需要先验信息来初始化区域，要么计算复杂，要么无法同时建立颜色一致性和空间连通性。在这里，我们将分段问题表示为单调波在吸收介质中具有变化的前沿速度的单调波传播。我们迭代地从选定的基点发出波。在一个基点，数据的局部方差达到最小值，这表明该基点是其局部邻域的合适代表。我们通过应用分层梯度算子来确定局部方差。波的速度取决于前面的点与波的当前覆盖范围的颜色相似度，以及边缘信息。因此，波在各向异性的空间颜色空间中前进。吸收功能充当波阵面的停止标准。我们利用快速行进方法来求解Eikonal方程，以找到波浪的传播时间。我们的方法优于基于链接的区域增长技术，因为它可以防止泄漏并在不使边界过度平滑的情况下在该区域上施加紧凑性。此外，我们可以应对尖锐的角落和拓扑变化。自动分割方法是欧拉式的，因此计算效率高。我们将结果与非欧拉方法进行了比较，该方法还评估了多波的到达时间。我们的实验说明了该方法的鲁棒性，准确性和有效性。

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