Segmentation of digital microscopy data for the analysis of defect structures in materials using nonlinear diffusions

Landis M. Huffman; Jeff Simmons; Ilya Pollak

doi:10.1117/12.777232

26 February 2008 Segmentation of digital microscopy data for the analysis of defect structures in materials using nonlinear diffusions

Landis M. Huffman, Jeff Simmons, Ilya Pollak

Author Affiliations +

Proceedings Volume 6814, Computational Imaging VI; 68140B (2008) https://doi.org/10.1117/12.777232
Event: Electronic Imaging, 2008, San Jose, California, United States

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.

Citation Download Citation

Landis M. Huffman, Jeff Simmons, and Ilya Pollak "Segmentation of digital microscopy data for the analysis of defect structures in materials using nonlinear diffusions", Proc. SPIE 6814, Computational Imaging VI, 68140B (26 February 2008); https://doi.org/10.1117/12.777232

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