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Proceedings Paper

Segmentation of digital microscopy data for the analysis of defect structures in materials using nonlinear diffusions
Author(s): Landis M. Huffman; Jeff Simmons; Ilya Pollak
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Paper Abstract

We apply stabilized inverse diffusion equations (SIDEs) to segment microscopy images of materials to aid in analysis of defects. We extend SIDE segmentation methods and demonstrate the effectiveness of our approaches to two material analysis tasks. We first develop a method to successfully isolate the textured area of a solidification defect to pixel accuracy. The second task involves utilizing multiple illuminations of the same structure of a polycrystalline alloy. Our novel approach features the fusion of data extracted from each of these images to create a composite segmentation which effectively represents all texture boundaries visible in any of the images. These two methods both propose new techniques to incorporate multiple images to produce segmentations.

Paper Details

Date Published: 26 February 2008
PDF: 9 pages
Proc. SPIE 6814, Computational Imaging VI, 68140B (26 February 2008); doi: 10.1117/12.777232
Show Author Affiliations
Landis M. Huffman, Purdue Univ. (United States)
Jeff Simmons, Air Force Research Lab. (United States)
Ilya Pollak, Purdue Univ. (United States)


Published in SPIE Proceedings Vol. 6814:
Computational Imaging VI
Charles A. Bouman; Eric L. Miller; Ilya Pollak, Editor(s)

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