论文标题
基于图形形态转化的骨骼化和重建
Skeletonization and Reconstruction based on Graph Morphological Transformations
论文作者
论文摘要
像素邻接图上的多尺度形状骨架化是图像处理，计算机视觉和数据挖掘领域中的一个高级有趣的研究主题。以前在该领域的作品几乎集中在图顶点上。我们提出了基于与当前节点的转换相反的边缘的基于新型结构化的图形形态转换，并将其用于部署由图表示的红外热图像的骨架化和重建。这种方法的优点是，在形态操作的这种定义中，许多广泛使用的基于路径的方法可用。例如，我们使用距离图和图像森林变换（IFT）作为两种基于路径的方法用于计算图像的骨架。此外，还讨论了Maragos等人（2013）提出的关于图形骨骼化方法的连通性提出的开放问题，并且在通常的情况下很难确定。
Multiscale shape skeletonization on pixel adjacency graphs is an advanced intriguing research subject in the field of image processing, computer vision and data mining. The previous works in this area almost focused on the graph vertices. We proposed novel structured based graph morphological transformations based on edges opposite to the current node based transformations and used them for deploying skeletonization and reconstruction of infrared thermal images represented by graphs. The advantage of this method is that many widely used path based approaches become available within this definition of morphological operations. For instance, we use distance maps and image foresting transform (IFT) as two main path based methods are utilized for computing the skeleton of an image. Moreover, In addition, the open question proposed by Maragos et al (2013) about connectivity of graph skeletonization method are discussed and shown to be quite difficult to decide in general case.
