A fast algorithm for Euclidean distance maps of a 2-D binary image
Information Processing Letters
An optimal parallel algorithm for the Euclidean distance maps of 2-D binary images
Information Processing Letters
Strategies for image segmentation combining region and boundary information
Pattern Recognition Letters
Segmentation of brush strokes by saliency preserving dual graph contraction
Pattern Recognition Letters - Special issue: Graph-based representations in pattern recognition
Shape recovery algorithms using level sets in 2-D/3-D medical imagery: a state-of-the-art review
IEEE Transactions on Information Technology in Biomedicine
Reconstruction method of foam structures from MRI imaging
ICOSSSE'08 Proceedings of the 7th WSEAS international conference on System science and simulation in engineering
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We discuss a method to reconstruct an approximate two-dimensional foam structure from an incomplete image using the extended Potts Model on a pinned lattice. The initial information consists of the positions of the vertices only. We locate the centers of the bubbles using the Euclidean distance-map construction and assign at each vertex position a continuous pinning field with a potential falling off as 1/r. We nucleate a bubble at each center using the extended Potts Model and let the structure evolve under the constraint of scaled target areas until the bubbles contact each other. The target area constraint and pinning centers prevent further coarsening. We then turn the area constraint off and let the edges relax to a minimum energy configuration. The result is a reconstructed structure very close to the simulation. We repeated this procedure for various stages of the coarsening of the same simulated foam and investigated the simulation and reconstruction dynamics, topology and area distribution, finding that they agreed to good accuracy.