Neighborhoods for distance transformations using ordered propagation
CVGIP: Image Understanding
The vector distance transform in two and three dimensions
CVGIP: Graphical Models and Image Processing
The Euclidean distance transform in arbitrary dimensions
Pattern Recognition Letters
On digital distance transforms in three dimensions
Computer Vision and Image Understanding
A List-Processing Approach to Compute Voronoi Diagrams and the Euclidean Distance Transform
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast Euclidean distance transformation by propagation using multiple neighborhoods
Computer Vision and Image Understanding
Geometry of Digital Spaces
Linear Time Euclidean Distance Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Generating distance maps with neighbourhood sequences
DGCI'06 Proceedings of the 13th international conference on Discrete Geometry for Computer Imagery
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The discrete Euclidean distance transform is applied to grids with non-cubic voxels, the face-centered cubic (fcc) and body-centered cubic (bcc) grids. These grids are three-dimensional generalizations of the hexagonal grid. Raster scanning and contour processing techniques are applied using different neighbourhoods. When computing the Euclidean distance transform, some voxel configurations produce errors. The maximum errors for the two different grids and neighbourhood sizes are analyzed and compared with the cubic grid.