Curvature-driven volumetric segmentation of binary shapes: An application to snow microstructure analysis

Many three-dimensional (3-D) image-based studies concerning granular and sintered materials require a description of the observed microstructures in terms of individual grains. We propose a robust segmentation algorithm which identify groove regions on the object's surface in order to locate po...

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Main Authors: Wang, X., Gillibert, L., Flin, F., Coeurjolly, D.
Format: Conference Proceeding
Language:English
Subjects:
Euclidean distance
Image segmentation
Labeling
Materials
Shape
Snow
Surface morphology
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creator Wang, X.
Gillibert, L.
Flin, F.
Coeurjolly, D.
description Many three-dimensional (3-D) image-based studies concerning granular and sintered materials require a description of the observed microstructures in terms of individual grains. We propose a robust segmentation algorithm which identify groove regions on the object's surface in order to locate possible grain boundaries in the object's volume. The algorithm relies on the volumetric propagation via Voronoi labeling of curvature information from the surface into the object 1 .
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source IEEE Xplore All Conference Series
subjects Euclidean distance
Image segmentation
Labeling
Materials
Shape
Snow
Surface morphology
title Curvature-driven volumetric segmentation of binary shapes: An application to snow microstructure analysis
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