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Memorias de investigación
Communications at congresses:
Image sub-segmentation by PFCM and Artificial Neural Networks to detect pore space in 2D and 3D CT soil images
Year:2011
Research Areas
  • Engineering
Information
Abstract
The image by Computed Tomography is a non-invasive alternative for observing soil structures, mainly pore space. The pore space correspond in soil data to empty or free space in the sense that no material is present there but only fluids, the fluid transport depend of pore spaces in soil, for this reason is important identify the regions that correspond to pore zones. In this paper we present a methodology in order to detect pore space and solid soil based on the synergy of the image processing, pattern recognition and artificial intelligence. The mathematical morphology is an image processing technique used for the purpose of image enhancement. In order to find pixels groups with a similar gray level intensity, or more or less homogeneous groups, a novel image sub-segmentation based on a Possibilistic Fuzzy c-Means (PFCM) clustering algorithm was used. The Artificial Neural Networks (ANNs) are very efficient for demanding large scale and generic pattern recognition applications for this reason finally a classifier based on artificial neural network is applied in order to classify soil images in two classes, pore space and solid soil respectively.
International
Si
Congress
European Geosciences Union General Assembly (EGU 2011)
960
Place
Viena, Austria
Reviewers
Si
ISBN/ISSN
1607-7962
Start Date
03/04/2011
End Date
08/04/2011
From page
11829
To page
11829
8th EGU General Assembly. Geophysical Research Abstracts, 13, 8656 (2011). [http://www.geophysical-research-abstracts.net]
Participants
  • Autor: Joel Quintanilla Dominguez (UPM)
  • Autor: María Guadalupe Cortina Januchs (UPM)
  • Autor: Benjamín Ojeda Magaña (UPM)
  • Autor: Antonio Vega Corona (Universidad de Guanajuato. México)
  • Autor: Diego Andina De la Fuente (UPM)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Grupo de Automatización en Señal y Comunicaciones (GASC)
  • Departamento: Señales, Sistemas y Radiocomunicaciones
S2i 2019 Observatorio de investigación @ UPM con la colaboración del Consejo Social UPM
Cofinanciación del MINECO en el marco del Programa INNCIDE 2011 (OTR-2011-0236)
Cofinanciación del MINECO en el marco del Programa INNPACTO (IPT-020000-2010-22)