Ju Tao, Baker Matthew L, Chiu Wah
Washington University, St. Louis, USA.
Comput Aided Des. 2007 May;39(5):352-360. doi: 10.1016/j.cad.2007.02.006.
Skeletons are important shape descriptors in object representation and recognition. Typically, skeletons of volumetric models are computed using iterative thinning. However, traditional thinning methods often generate skeletons with complex structures that are unsuitable for shape description, and appropriate pruning methods are lacking. In this paper, we present a new method for computing skeletons of volumetric models by alternating thinning and a novel skeleton pruning routine. Our method creates a family of skeletons parameterized by two user-specified numbers that determine respectively the size of curve and surface features on the skeleton. As demonstrated on both real-world models and protein images in bio-medical research, our method generates skeletons with simple and meaningful structures that are particularly suitable for describing cylindrical and plate-like shapes.
骨架是物体表示和识别中重要的形状描述符。通常，体模型的骨架是通过迭代细化来计算的。然而，传统的细化方法往往会生成结构复杂、不适合形状描述的骨架，并且缺乏合适的修剪方法。在本文中，我们提出了一种通过交替细化和一种新颖的骨架修剪程序来计算体模型骨架的新方法。我们的方法创建了一族由两个用户指定的数字参数化的骨架，这两个数字分别决定了骨架上曲线和表面特征的大小。正如在真实世界模型和生物医学研究中的蛋白质图像上所展示的那样，我们的方法生成的骨架具有简单且有意义的结构，特别适合描述圆柱形和板状形状。
