Fast parallel thinning algorithms: parallel speed and connectivity preservation
Communications of the ACM
Simple connectivity is not locally computable for connected 3D images
Computer Vision, Graphics, and Image Processing
A new characterization of three-dimensional simple points
Pattern Recognition Letters
Simple points, topological numbers and geodesic neighborhoods in cubic grids
Pattern Recognition Letters
Topology-preserving deformations of two-valued digital pictures
Graphical Models and Image Processing
A 3D 6-subiteration thinning algorithm for extracting medial lines
Pattern Recognition Letters
Sequential Operations in Digital Picture Processing
Journal of the ACM (JACM)
Connectivity in Digital Pictures
Journal of the ACM (JACM)
A Sequential 3D Thinning Algorithm and Its Medical Applications
IPMI '01 Proceedings of the 17th International Conference on Information Processing in Medical Imaging
Directional 3D Thinning Using 8 Subiterations
DCGI '99 Proceedings of the 8th International Conference on Discrete Geometry for Computer Imagery
DGCI '02 Proceedings of the 10th International Conference on Discrete Geometry for Computer Imagery
A New 3D 6-Subiteration Thinning Algorithm Based on P-Simple Points
DGCI '02 Proceedings of the 10th International Conference on Discrete Geometry for Computer Imagery
A concise characterization of 3D simple points
Discrete Applied Mathematics
A comparative discussion of distance transforms and simple deformations in digital image processing
Machine Graphics & Vision International Journal
Image Analysis and Mathematical Morphology
Image Analysis and Mathematical Morphology
Skeletal curves of 3D astrocyte samples
Machine Graphics & Vision International Journal
Branch voxels and junctions in 3d skeletons
IWCIA'06 Proceedings of the 11th international conference on Combinatorial Image Analysis
Three-dimensional thinning algorithms on graphics processing units and multicore CPUs
Concurrency and Computation: Practice & Experience
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Topological thinning includes tests for voxels to be simple or not. A point (pixel or voxel) is simple if the change of its image value does not change the topology of the image. A problem with topology preservation in 3D is that checking voxels to be simple is more complex and time consuming than in 2D. In this paper, we review some characterizations of simple voxels and we propose a new methodology for identifying non-simple points. We implemented our approach by modifying an existing 3D thinning algorithm and achieved an improved running time.