Abstract
Quantitative and qualitative description of particles is one of the most important tasks in the Electron Microscopy (EM) analysis. In this paper, we present an algorithm for identifying ball-like nanostructures of gahnite in the Transmission Electron Microscopy (TEM) images. Our solution is based on the cross-entropy clustering which allows to count and measure disk-like objects which are not necessary disjoint or with not smooth borders.
Keywords
- Electron Microscopy Image
- Mathematical Morphology
- European Regional Development Fund
- Transmission Electron Microscopy Picture
- Circle Detection
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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© 2013 Springer International Publishing Switzerland
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Spurek, P., Tabor, J., Zając, E. (2013). Detection of Disk-Like Particles in Electron Microscopy Images. In: Burduk, R., Jackowski, K., Kurzynski, M., Wozniak, M., Zolnierek, A. (eds) Proceedings of the 8th International Conference on Computer Recognition Systems CORES 2013. Advances in Intelligent Systems and Computing, vol 226. Springer, Heidelberg. https://doi.org/10.1007/978-3-319-00969-8_40
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DOI: https://doi.org/10.1007/978-3-319-00969-8_40
Publisher Name: Springer, Heidelberg
Print ISBN: 978-3-319-00968-1
Online ISBN: 978-3-319-00969-8
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