This paper proposes a new approach for skeletonization based on the skeleton strength map (SSM) caculated by Euclidean distance transform of a binary image. After the distance transform and gradient are computed, isotropic diffusion is performed on the gradient vector field and the skeleton strength map is computed from the diffused vector field. A critical point set is then selected from local maxima of the SSM. The critical points are located on significant visual parts of the object. The skeleton is obtained by connecting the critical points with geodesic paths. This approach overcomes intrinsic drawbacks of distance transform based skeletons, since it yields stable and connected skeletons without losing significant visual parts.
REF used skeleton strength maps (SSM) which are calculated by the isotropic diffusion of the Euclidian distance transformation of binary images and their gradient.
Skeletonization using SSM of the Distance Transform
2007 IEEE International Conference on Image Processing
2007 IEEE International Conference on Image Processing
Mathematics Computer Science