Morphological methods in image and signal processing
Morphological methods in image and signal processing
Local distances for distance transformations in two and three dimensions
Pattern Recognition Letters
Sequential Operations in Digital Picture Processing
Journal of the ACM (JACM)
Morphological Image Processing: Architecture and VLSI Design
Morphological Image Processing: Architecture and VLSI Design
Logic Minimization Algorithms for VLSI Synthesis
Logic Minimization Algorithms for VLSI Synthesis
On Skeletonization in 4D Images
SSPR '96 Proceedings of the 6th International Workshop on Advances in Structural and Syntactical Pattern Recognition
Image Analysis and Mathematical Morphology
Image Analysis and Mathematical Morphology
Hexagonal Parallel Pattern Transformations
IEEE Transactions on Computers
Morphological Operations in Recursive Neighbourhoods
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
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This paper describes a practical approach to mathematical morphology and ways to implement its operations. The first chapters treat a formalism that has the potential of implementing morphological operations on binary images of arbitrary dimensions. The formalism is based on sets of structuring elements for hit-or-miss transforms whereas each structuring element actually describes a shape primitive. The formalism is applied to two and three dimensional binary images and the paper includes structuring elements for topology preserving thinning or skeletonization and various skeleton variants. The generation of shape primitive detecting masks is treated as well as their application in segmentation, accurate measurement and conditions for topology preserving. The formalism is expanded to four-dimensional images and elaborates on the extension of 3D skeletonization to 4D skeletonization. A short excursion was made to methods based on 3D and 4D Euler-cluster count methods.