Detail publikace

Segmentation of multi-phase object applying trainable segmentation

KALASOVÁ, D. MAŠEK, J. ZIKMUND, T. SPURNÝ, P. HALODA, J. BURGET, R. KAISER, J.

Originální název

Segmentation of multi-phase object applying trainable segmentation

Typ

článek v časopise - ostatní, Jost

Jazyk

angličtina

Originální abstrakt

In X-ray computed tomography (CT), post-processing of acquired data is necessary for obtaining quantitative information of the object. As initial step, it is necessary to segment different materials of the sample. The easiest and standardly used segmentation method is based on global thresholding according to histogram, but it works well only if histogram with multi-modal character where the intensity is distributed to the separate count peaks. In this paper, we show the possibility of segmentation of tomographic data using trainable segmentation on data, where standard global thresholding fails. Trainable segmentation is a method that combines a collection of machine learning algorithms (decision tree, neural network, etc.) with a set of selected image features to produce binary pixel-based segmentation. This method is demonstrated on a sample of meteorite consisting of multiple phases (silicates, metals, sulphides), where knowledge of volumes of different materials is important for non-destructive study of modal phase composition, meteorite microstructures and identification of lithologies with different origin and evolution.

Klíčová slova

segmentation, trainable segmentation, machine learning, image processing

Autoři

KALASOVÁ, D.; MAŠEK, J.; ZIKMUND, T.; SPURNÝ, P.; HALODA, J.; BURGET, R.; KAISER, J.

Vydáno

9. 2. 2017

Nakladatel

NDT.net

ISSN

1435-4934

Periodikum

The e-Journal of Nondestructive Testing

Číslo

2017

Stát

Spolková republika Německo

Strany od

1

Strany do

6

Strany počet

6

URL

http://www.ndt.net/events/iCT2017/app/content/index.php?eventID=37

BibTex

@article{BUT133386,
  author="Dominika {Kalasová} and Jan {Mašek} and Tomáš {Zikmund} and Pavel {Spurný} and Jakub {Haloda} and Radim {Burget} and Jozef {Kaiser}",
  title="Segmentation of multi-phase object applying trainable segmentation",
  journal="The e-Journal of Nondestructive Testing",
  year="2017",
  number="2017",
  pages="1--6",
  issn="1435-4934",
  url="http://www.ndt.net/events/iCT2017/app/content/index.php?eventID=37"
}