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Geometric Morphology of Granular Materials

B. R. Schlei·L. Prasad·A. N. Skourikhine
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Abstract

We present a new method to transform the spectral pixel information of a micrograph into an affine geometric description, which allows us to analyze the morphology of granular materials. We use spectral and pulse-coupled neural network based segmentation techniques to generate blobs, and a newly developed algorithm to extract dilated contours. A constrained Delaunay tesselation of the contour points results in a triangular mesh. This mesh is the basic ingredient of the Chodal Axis Transform, which provides a morphological decomposition of shapes. Such decomposition allows for grain separation and the efficient computation of the statistical features of granular materials.

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B. R. Schlei, L. Prasad, A. N. Skourikhine. 2000-06-30. Geometric Morphology of Granular Materials. https://doi.org/10.1117/12.404821

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