Skeleton extraction method based on distance transform

The skeleton can describe an object's geometry and topology with few data, and is applied in a variety of tasks in computer vision. While common distance transform can hardly guarantee the connectivity property of the skeleton, or thinning algorithms for skeleton extraction can't guarantee the accuracy. In this paper, a new skeleton extraction method is proposed. Based on Euclidean distance transform, the seeds of the skeleton are determined according to the number of greater direction. And then a two-step skeleton growth is employed to obtain connected and one-pixel width skeleton. The experiments prove that the proposed algorithm not only has low time complexity, but also guarantees the connectivity and one-pixel width of the skeleton.