Image processing for porous media characterization

Ahmad Almhdie (1) , Rachid Jennane (2) , Olivier Rozenbaum (3) , Eric Lespessailles (4) , Christophe Léger (1)

1 PRISME - Laboratoire Pluridisciplinaire de Recherche en Ingénierie des Systèmes, Mécanique et Energétique
2 LESI - Laboratoire d'électronique, signaux, images
3 ISTO - Institut des Sciences de la Terre d'Orléans
4 Caractérisation du tissu osseux par imagerie : techniques et applications

In digital image processing, skeletonization is a valuable technique for the characterization of complex 3D porous media, such as bone, stone and soils. 3D thinning algorithms are usually used to extract one-voxel wide skeleton from 3D porous objects while preserving the topological information. Models based on simplified skeletons have been shown to be efficient in retrieving morphological information from large scale disordered objects at a local level. In this paper, we present a series of 3D skeleton-based image processing techniques for evaluating the micro-architecture of large scale disordered porous media. The proposed hybrid skeleton method combines curve and surface thinning methods with the help of an enhanced shape classification algorithm. Results on two different porous objects demonstrate the ability of the hybrid skeleton method to provide significant topological and morphological information.

Mots clés: Classification; thinning; segmentation

Domaines: Traitement du signal et de l'image [eess.SP]; Traitement du signal et de l'image [eess.SP]

Ahmad Almhdie, Rachid Jennane, Olivier Rozenbaum, Eric Lespessailles, Christophe Léger. Image processing for porous media characterization. Mamern'11, May 2011, Saidia, Morocco. pp.82-94. ⟨hal-00608117⟩