Digital Distance Transforms in 3D Images Using Information from Neighbourhoods up to 5×5×5

摘要

A 3D distance image, or a distance transform, is an image where each feature voxel is labeled with the distance to its closest nonfeature voxel. Distance transforms are useful for many binary (shape) image analysis tasks. The distance transform can be computed by propagating local distance information between neighboring voxels. In a weighted distance transform, the local distances are optimized to make the distance transform more stable under rotation. We present results from optimization for 3D images when using from one to six local distances, all in the 5×5×5 neighborhood of a voxel.