Geometric morphology of cellular solids

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Description

We demonstrate how to derive morphological information from micrographs, i.e., grey-level images, of polymeric foams. The segmentation of the images is performed by applying a pulse-coupled neural network. This processing generates blobs of the foams walls/struts and voids, respectively. The contours of the blobs and their corresponding points form the input to a constrained Delaunay tessellation, which provides an unstructured grid of the material under consideration. The subsequently applied Chordal Axis Transform captures the intrinsic shape characteristics, and facilitates the identification and localization of key morphological features. While stochastic features of the polymeric foams struts/walls such as areas, aspect ratios, ... continued below

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7 p.

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Schlei, B. R. (Bernd R.); Prasad, L. (Lakshaman) & Skourikhine, A. N. (Alexei N.) January 1, 2001.

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Description

We demonstrate how to derive morphological information from micrographs, i.e., grey-level images, of polymeric foams. The segmentation of the images is performed by applying a pulse-coupled neural network. This processing generates blobs of the foams walls/struts and voids, respectively. The contours of the blobs and their corresponding points form the input to a constrained Delaunay tessellation, which provides an unstructured grid of the material under consideration. The subsequently applied Chordal Axis Transform captures the intrinsic shape characteristics, and facilitates the identification and localization of key morphological features. While stochastic features of the polymeric foams struts/walls such as areas, aspect ratios, etc., already can be computed at this stage, the foams voids require further geometric processing. The voids are separated into single foam cells. This shape manipulation leads to a refinement of the initial blob contours, which then requires the repeated application of the constrained Delaunay tessellation and Chordal Axis Transform, respectively. Using minimum enclosing rectangles for each foam cell, finally the stochastic features of the foam voids are computed.

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7 p.

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  • Submitted to: Proceedings SPIE 2001 Meeting, San Diego, CA, July 29-August 3, 2001

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  • Report No.: LA-UR-01-3912
  • Grant Number: none
  • Office of Scientific & Technical Information Report Number: 975644
  • Archival Resource Key: ark:/67531/metadc931623

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Office of Scientific & Technical Information Technical Reports

Reports, articles and other documents harvested from the Office of Scientific and Technical Information.

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  • January 1, 2001

Added to The UNT Digital Library

  • Nov. 13, 2016, 7:26 p.m.

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  • Dec. 9, 2016, 11:38 p.m.

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Schlei, B. R. (Bernd R.); Prasad, L. (Lakshaman) & Skourikhine, A. N. (Alexei N.). Geometric morphology of cellular solids, article, January 1, 2001; United States. (digital.library.unt.edu/ark:/67531/metadc931623/: accessed October 19, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.