Distance transformations in digital images
Computer Vision, Graphics, and Image Processing
Finding local maxima in a pseudo-Euclidean distance transform
Computer Vision, Graphics, and Image Processing
The Euclidean distance transform in arbitrary dimensions
Pattern Recognition Letters
Discrete distance operator on rectangular grids
Pattern Recognition Letters
On digital distance transforms in three dimensions
Computer Vision and Image Understanding
Sequential Operations in Digital Picture Processing
Journal of the ACM (JACM)
Synthesising Objects and Scenes Using the Reverse Distance Transformation in 2D and 3D
ICIAP '95 Proceedings of the 8th International Conference on Image Analysis and Processing
Weighted Distance Transforms for Images Using Elongated Voxel Grids
DGCI '02 Proceedings of the 10th International Conference on Discrete Geometry for Computer Imagery
Weighted Distance Transforms in Rectangular Grids
ICIAP '01 Proceedings of the 11th International Conference on Image Analysis and Processing
Distance transforms for three-dimensional grids with non-cubic voxels
Computer Vision and Image Understanding
Distance transforms for three-dimensional grids with non-cubic voxels
Computer Vision and Image Understanding
3-D chamfer distances and norms in anisotropic grids
Image and Vision Computing
Distance transformation on two-dimensional irregular isothetic grids
DGCI'08 Proceedings of the 14th IAPR international conference on Discrete geometry for computer imagery
A novel algorithm for distance transformation on irregular isothetic grids
DGCI'09 Proceedings of the 15th IAPR international conference on Discrete geometry for computer imagery
Fast distance transformation on irregular two-dimensional grids
Pattern Recognition
Separable algorithms for distance transformations on irregular grids
Pattern Recognition Letters
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Weighted distance transforms in volume (3D) images using a voxel grid with equal resolution along two axes and lower along the third are investigated. The weights (neighbour distances) in a local neighbourhood of size 3 × 3 × 3 are optimized by minimizing the maximum error in a cubic image.