SKELETONIZATION WITH PARTICLE FILTERS
Yuchun Tang, Xiang Bai, Xing‐Wei Yang, Liang Lin, Shuwei Liu, Longin Jan Latecki · International Journal of Pattern Recognition and Artificial Intelligence · 2010
We present a novel method to obtain high quality skeletons of binary shapes. The obtained skeletons are connected and one pixel thick. They do not require any pruning or any other post-processing. The computation is composed of two major parts. First, a small set of salient contour points is computed. We use Discrete Curve Evolution, but any other robust method could be used. Second, particle filters are used to obtain the skeleton. The main idea is that the particles walk along the skeletal paths between pairs of the salient points. We provide experimental results that clearly demonstrate that the proposed method significantly outperforms other well-known methods for skeleton computation. Moreover, we propose an extension of our method to computing skeletons of gray level images and provide promising experimental results.