Memorias de investigación
Research Publications in journals:
Identification of pore spaces in 3D CT soil images using a PFCM partitional clustering

Research Areas
  • Information technology and adata processing,
  • Image segmentation

Recent advances in non-destructive imaging techniques, such as X-ray computed tomography (CT), make it possible to analyse pore space features from the direct visualisation from soil structures. A quantitative characterisation of the three-dimensional solid-pore architecture is important to understand soil mechanics, as they relate to the control of biological, chemical, and physical processes across scales. This analysis technique therefore offers an opportunity to better interpret soil strata, as new and relevant information can be obtained. In this work, we propose an approach to automatically identify the pore structure of a set of 200-2D images that represent slices of an original 3D CT image of a soil sample, which can be accomplished through non-linear enhancement of the pixel grey levels and an image segmentation based on a PFCM (Possibilistic Fuzzy C-Means) algorithm. Once the solids and pore spaces have been identified, the set of 200-2D images is then used to reconstruct an approximation of the soil sample by projecting only the pore spaces. This reconstruction shows the structure of the soil and its pores, which become more bounded, less bounded, or unbounded with changes in depth. If the soil sample image quality is sufficiently favourable in terms of contrast, noise and sharpness, the pore identification is less complicated, and the PFCM clustering algorithm can be used without additional processing; otherwise, images require pre-processing before using this algorithm. Promising results were obtained with four soil samples, the first of which was used to show the algorithm validity and the additional three were used to demonstrate the robustness of our proposal. The methodology we present here can better detect the solid soil and pore spaces on CT images, enabling the generation of better 2D?3D representations of pore structures from segmented 2D images.
Impact factor JCR
Impact info
Datos JCR del año 2012
Journal number
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  • Autor: Benjamín Ojeda Magaña UPM
  • Autor: Joel Quintanilla Domínguez UPM
  • Autor: Ruben Ruelas Universidad de Guadalajara
  • Autor: Ana Maria Tarquis Alfonso UPM
  • Autor: Leopoldo Gómez Barba Universidad de Guadalajara
  • 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
  • Departamento: Matemática Aplicada