A connected-component-labeling-based approach to virtual porosimetry q Jorge Ernesto Rodríguez a,⇑ , Irving Cruz c , Eduard Vergés b,c , Dolors Ayala b,c a Universidad de Carabobo, Facultad de Ciencias y Tecnología (FACYT), CEMVICC, Av. Universidad, Campus Bárbula, 2005 Valencia, Venezuela b Institut de Bioenginyeria de Catalunya, Barcelona, Spain c Universitat Politècnica de Catalunya, Barcelona, Spain article info Article history: Received 17 August 2010 Received in revised form 27 April 2011 Accepted 14 June 2011 Available online 22 June 2011 Keywords: Virtual MIP Micro CT Porous media Pore map Skeleton abstract Analyzing the pore-size distribution of porous materials, made up of an aggregation of interconnected pores, is a demanding task. Mercury intrusion porosimetry (MIP) is a phys- ical method that intrudes mercury into a sample at increasing pressures to obtain a pore- size histogram. This method has been simulated in-silice with several approaches requiring prior computation of a skeleton. We present a new approach to simulate MIP that does not require skeleton computation. Our method is an iterative process that considers the diameters corresponding to pres- sures. At each iteration, geometric tests detect throats for the corresponding diameter and a CCL process collects the region invaded by the mercury. Additionally, a new decom- position model called CUDB, is used. This is suitable for computing the throats and performs better with the CCL algorithm than a voxel model. Our approach obtains the pore-size distribution of the porous medium, and the corresponding pore graph. Ó 2011 Elsevier Inc. All rights reserved. 1. Introduction Geometrical and topological representations of the internal structures of porous material samples are neces- sary to evaluate their physical properties. Such samples have two disjoint spaces – pore space and solid space – and can thus be represented as 3D binary images. The pore space, in turn, is made up of a collection of pores that can be intuitively defined as local openings that can be inter- connected by narrow apertures called throats [1]. Studying the properties of porous materials is of great utility in several disciplines. In medicine, they are used to evaluate the degree of osteoporosis and the adequacy of synthetic biomaterial implants for bone regeneration, among other applications. Bone regeneration occurs in the cavities of the implants, where blood can flow. Bioma- terial implants can be designed as tissue scaffolds, that is, extracellular matrices onto which cells can attach and then grow and form new tissues [2,3]. In geology, a rock’s por- ous structure is related to its oil-bearing and hydrological properties [4]. Likewise, brine inclusions in sea ice can be formalized in terms of their morphology and connectivity [5]. In engineering, the durability of cementitious materials is associated with certain mechanical and transport prop- erties that can be evaluated based on the properties of the pore space [6]. Common structural parameters include density, poros- ity, surface area, pore-size distribution, connectivity and permeability [7]. Density and porosity are the ratio be- tween solid and pore space volume with regard to the vol- ume of the sample as a whole. Effective porosity is the porosity that takes into account the pore space connected to the exterior without considering internal cavities. Sur- face area is the area between the two phases and connec- tivity is related to the genus of the solid space and can be computed from the Euler characteristic [8–10]. Pore-size distribution is used to evaluate the suitability of biomaterials to form new tissues, as well as to under- stand fluid distribution in gas- or oil-bearing rocks. This 1524-0703/$ - see front matter Ó 2011 Elsevier Inc. All rights reserved. doi:10.1016/j.gmod.2011.06.001 q This paper has been recommended for acceptance by Jarek Rossignac and Eitan Grinspun. ⇑ Corresponding author. Fax: +58 2416004000x375203. E-mail addresses: jrodrigu@uc.edu.ve (J.E. Rodríguez), icruz@lsi. upc.edu (I. Cruz), everges@lsi.upc.edu (E. Vergés), dolorsa@lsi.upc.edu (D. Ayala). Graphical Models 73 (2011) 296–310 Contents lists available at ScienceDirect Graphical Models journal homepage: www.elsevier.com/locate/gmod