Skeleton is one of the simplest but powerful tools for shape representation and analysis, which encodes the original shape by one less dimension but can retain the topological information well. Inspired by the observation that the skeleton also serves as a symmetry axis, we propose to compute the skeleton by symmetry analysis of the given shape. In implementation, we define the skeletal saliency map by using the projection symmetry measurement. Firstly, the primitive boundary is extracted. Then, for each pixel p in the shape, we project its four neighboring pixels onto the boundary. The saliency of p is estimated by the maximum distance along the boundary between the two projections. Finally, a clean skeleton is reported by a simple truncation operation. The proposed method can produce a two-pixel-wide skeleton with correct topology and avoid any additional post-processing. Furthermore, it is also robust to boundary noise. Extensive experiment results validate these nice properties of the proposed method, which shows that it outperforms the state-of-the-art methods.

骨架是用于形状表示和分析的最简单但功能强大的工具之一，它可以将原始形状减少一维编码，但可以很好地保留拓扑信息。受骨架也可以作为对称轴的观察的启发，我们建议通过对给定形状的对称分析来计算骨架。在实现中，我们通过使用投影对称性测量来定义骨骼显着图。首先，提取原始边界。然后，对于形状中的每个像素p，我们将其四个相邻像素投影到边界上。p的显着性通过沿着两个投影之间的边界的最大距离来估算。最后，通过简单的截断操作报告了干净的骨架。所提出的方法可以产生具有正确拓扑结构的两像素宽的骨架，并避免任何额外的后处理。此外，它对边界噪声也很鲁棒。大量的实验结果验证了所提出方法的这些优良特性，表明它优于最新方法。