Characterization of pore space using a non-hierarchical decomposition model

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

B io-CAD and in-silico experimentation is getting a growing interest in biomedical applications, where scientific data coming from images of real samples are used to evaluate physical properties. In this sense, analyzing the pore-size distribution is a demanding task to help to interpret the characteristics of porous materials by partitioning it into its constituent pores. Pores are defined intuitively as local openings that can be interconnected by narrow apertures called throats that control a non-wetting phase invasion in a physical method. There are several approaches to characterize the pore space in terms of its constituent pores, several of them requiring prior computation of a skeleton. This paper presents a new approach to characterize the pore space, in terms of a pore-size distribution, which does not require the skeleton computation. Throats are identified using a new decomposition model that performs a 2D spatial partition of the object in a non-hierarchical sweep-based way consisting of a set of disjoint boxes. This approach enables the characterization of the pore space in terms of a pore-size distribution
Original languageEnglish
Title of host publication5th International Conference and Expo on Computer Graphics & Animation
PublisherSciTechnol
Pages34
Volume07
DOIs
Publication statusPublished - 26 Sep 2018

Publication series

NameJournal of Computer Engineering & Information Technology

Fingerprint Dive into the research topics of 'Characterization of pore space using a non-hierarchical decomposition model'. Together they form a unique fingerprint.

  • Cite this

    Cruz Matías, I. A. (2018). Characterization of pore space using a non-hierarchical decomposition model. In 5th International Conference and Expo on Computer Graphics & Animation (Vol. 07, pp. 34). (Journal of Computer Engineering & Information Technology). SciTechnol. https://doi.org/10.4172/2324-9307-C3-026