SKELETONIZATION OF GRAY-SCALE IMAGE FROM INCOMPLETE BOUNDARIES

Skeletonization of gray-scale images is a challenging problem in computer vision due to the difficulty of segmenting grayscale images to get the complete contour. Compared with previous skeletonization algorithms which use computational methods to avoid segmentation, this paper reveals that it is applicable to skeletonize gray-scale images from boundaries directly. We start from boundaries of gray-scale images and perform Euclidean Distance Transform on boundaries. Then we compute the gradient magnitude of the distance transforrn and perform isotropic vector diffusion. After diffusion, the Skeleton Strength Map (SSM) is computed and skeleton can be extracted from SSM. The experiments show that this method can obtain good performance from boundaries so long as major boundary segments are preserved.