A skeletonization algorithm using chamfer distance transformation adapted to rectangular grids

Many skeletonization methods based on distance transformation have been proposed. They are generally designed for square grids. However most industrial vision systems digitize images on rectangular grids. These images are then resampled to obtain square pixels. In this paper we propose a skeletonization algorithm directly adapted to rectangular grids. We use the efficient skeletonization method of Arcelli and Sanniti di Baja (1993), based on the Euclidean distance transform, and we adapt it to chamfer distances computed on rectangular grids. We propose some modifications to this algorithm. Some results are given and discussed.