An efficient and accurate algorithm for extracting a skeleton

The skeleton is an important feature in the representation of a shape in image analysis. In this paper, a non-iterative method is proposed, which is fast, efficient, and more importantly, is robust to boundary noise and rotation. Unnecessary branches and hairs, can be reduced by the adjustment of the residual distance and the skeleton can be represented in a hierarchical manner. The reconstruction error can also be estimated using the residual distance. A new definition of a skeleton and the criteria of being a skeleton point are introduced. The effect of boundary noise and curved boundary are investigated and compared to other skeletonization algorithms. Finally, the reconstruction of an object using its skeleton and the associated radii of the maximal disks is illustrated.