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Comparison of Common Segmentation Techniques Applied to Transmission Electron Microscopy Images

Published online by Cambridge University Press:  01 February 2011

Thomas Sadowski
Affiliation:
tommy91779@hotmail.com, Southernc Connecticut State University, Physics and Computer Science, 501 Crescent St, New Haven, CT, 06515, United States, (203) 392-5200
Christine C. Broadbridge
Affiliation:
broadbridge@southernct.edu, Southern Connecticut State University, Physics, 501 Crescent Street, New Haven, CT, 06515, United States
John Daponte
Affiliation:
dapontej1@southernct.edu, Southern Connecticut State University, Computer Science, 501 Crescent Street, New Haven, CT, 06515, United States
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Abstract

Nanoparticles are of interest in many applications since their decreased size may give them properties that are very different from bulk material. Often nanoparticle properties such as size (diameter) and size distribution are evaluated using transmission electron microscopy (TEM). These parameters, size and size distribution, can be more easily obtained from digitized TEM images by mapping particle signal to black and background pixel to white in a process known as thresholding then performing an algorithm known as a particle analysis. The goal of this study was to compare the ability of several popular thresholding algorithms to segment TEM images. Performance of the thresholding algorithms was evaluated through qualitative and quantitative measures. Results show that the choice of a thresholding algorithm will strongly affect the results obtained from particle analysis.

Type
Research Article
Copyright
Copyright © Materials Research Society 2007

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