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作者机构:Univ Orleans ISTO UMR 7327 F-45071 Orleans France Univ Orleans Hosp Orleans Lab I3MTO EA 4708 F-45032 Orleans France Univ Orleans PRISME Lab EA 4229 F-45067 Orleans France
出 版 物:《MATHEMATICS AND COMPUTERS IN SIMULATION》 (系统模拟中的数学与计算机)
年 卷 期:2014年第99卷
页 面:82-94页
核心收录:
学科分类:07[理学] 070104[理学-应用数学] 0835[工学-软件工程] 0701[理学-数学] 0812[工学-计算机科学与技术(可授工学、理学学位)]
主 题:Segmentation Skeleton Classification Topological and morphological information Porous media
摘 要:Different image processing techniques have recently been investigated for the characterization of complex porous media, such as bones, stones and soils. Among these techniques, 3D thinning algorithms are generally used to extract a one-voxel-thick 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 not only at a global level but also 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 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 proposed method to provide significant topological and morphological information. (C) 2013 IMACS. Published by Elsevier B.V. All rights reserved.