Computing distance transformations in convex and non-convex domains
Pattern Recognition
Finding local maxima in a pseudo-Euclidean distance transform
Computer Vision, Graphics, and Image Processing
Digital topology: introduction and survey
Computer Vision, Graphics, and Image Processing
Watersheds in Digital Spaces: An Efficient Algorithm Based on Immersion Simulations
IEEE Transactions on Pattern Analysis and Machine Intelligence
CVGIP: Graphical Models and Image Processing
A new characterization of three-dimensional simple points
Pattern Recognition Letters
Detection of 3-D Simple Points for Topology Preserving Transformations with Application to Thinning
IEEE Transactions on Pattern Analysis and Machine Intelligence
Analyzing nonconvex 2D and 3D patterns
Computer Vision and Image Understanding
On digital distance transforms in three dimensions
Computer Vision and Image Understanding
Sequential Operations in Digital Picture Processing
Journal of the ACM (JACM)
A three-dimensional holes closing algorithm
Pattern Recognition Letters
Simplifying curve skeletons in volume images
Computer Vision and Image Understanding
Finding Cavities and Tunnels in 3D Complex Objects
ICIAP '03 Proceedings of the 12th International Conference on Image Analysis and Processing
New Fusion Operations for Digitized Binary Images and Their Applications
IEEE Transactions on Pattern Analysis and Machine Intelligence
Journal of Visual Languages and Computing
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Entities such as object components, cavities, tunnels and concavities in 3D digital images can be useful in the framework of object analysis. For each object component, we first identify its convex deficiencies, by subtracting the object component from a covering polyhedron approximating the convex hull. Watershed segmentation is then used to decompose complex convex deficiencies into simpler parts, corresponding to individual cavities, concavities and tunnels of the object component. These entities are finally described by means of a representation system accounting for the shape features characterising them.