Voronoi Label N dimensions
Voronoi Label N
Tool for drawing a Voronoi label matrix given a set of centroids. Creates an N-D Voronoi diagram label matrix from input centroid coordinates. May be used directly on pixel coordinate centroids, or used on arbitrary numeric coordinate centroids with args 2-4.
Two methods are available:
-
"coordinates"
- uses a compute- and memory-intensive direct computation of nearest centroid to each element. Labels all elements, biased towards smaller valued labels when there is a tie. Complexity isO(M*N*P)
whereM
is the number of centroids,N
is the number of dimensions,P
is the number of elements in the output image. Suitable if Image Processing Toolbox is not available. -
"watershed"
- uses a faster, less-memory-intensive computation using optimized image processing algorithmsbwdist()
andwatershed()
. Prefer this method if Image Processing Toolbox is available, it is about twice as fast.
Usage:
- Pixel coordinates, call with 1st arg only, or with 1st and 5th (args 2-4 empty arrays).
- Arbitrary coordinates, call with 2nd arg to give shape, 3rd to give origin and 4th to scale pixels/voxels.
% direct
labels = voronoi_labeln(centroids) % implied shape
labels = voronoi_labeln(centroids, shape) % explicit shape
labels = voronoi_labeln(centroids, shape, [], px_len) % scale
labels = voronoi_labeln(centroids, shape, origin, []) % translate
labels = voronoi_labeln(centroids, shape, origin, px_len) % both
% watershed
labels = voronoi_labels(centroids, [], [], [], "watershed")
labels = voronoi_labels(centroids, shape, [], [], "watershed")
% ... etc.
Citar como
William Warriner (2024). Voronoi Label N dimensions (https://github.com/wwarriner/matlab_voronoi_labeln), GitHub. Recuperado .
Compatibilidad con la versión de MATLAB
Compatibilidad con las plataformas
Windows macOS LinuxEtiquetas
Agradecimientos
Inspirado por: createVoronoi(centroids,imageFilename), Convert Voronoi cells to region mask
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Versión | Publicado | Notas de la versión | |
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1.0.1.1 | Update title |
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1.0.1 | Watershed now behaves identically to direct compute, and about twice as fast. |
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1.0.0.1 | Added sample labelvolshow() image. |
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1.0.0 |
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