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Please use this identifier to cite or link to this item: http://hdl.handle.net/10373/128

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Title: Influence of image resolution and evaluation algorithm on estimates of the lacunarity of porous media
Authors: Pendleton, D. E.
Dathe, A.
Baveye, Philippe C.
Affiliation: University of Abertay Dundee. School of Contemporary Sciences
University of Abertay Dundee. SIMBIOS
Keywords: Image resolution
Porous materials
Granular materials
Fractals
Issue Date: Oct-2005
Publisher: American Physical Society
Type: Article
Refereed: peer-reviewed
Rights: (c)The American Physical Society. Published version available from http://link.aps.org/doi/10.1103/PhysRevE.72.041306
Citation: Pendleton, D.E., Dathe, A. and Beveye, P. 2005. Influence of image resolution and evaluation algorithm on estimates of the lacunarity of porous media. Physical Review E. 72(4)
Abstract: In recent years, experience has demonstrated that the classical fractal dimensions are not sufficient to describe uniquely the interstitial geometry of porous media. At least one additional index or dimension is necessary. Lacunarity, a measure of the degree to which a data set is translationally invariant, is a possible candidate. Unfortunately, several approaches exist to evaluate it on the basis of binary images of the object under study, and it is unclear to what extent the lacunarity estimates that these methods produce are dependent on the resolution of the images used. In the present work, the gliding-box algorithm of Allain and Cloitre [Phys. Rev. A 44, 3552 (1991)] and two variants of the sandbox algorithm of Chappard et al. [J. Pathol. 195, 515 (2001)], along with three additional algorithms, are used to evaluate the lacunarity of images of a textbook fractal, the Sierpinski carpet, of scanning electron micrographs of a thin section of a European soil, and of light transmission photographs of a Togolese soil. The results suggest that lacunarity estimates, as well as the ranking of the three tested systems according to their lacunarity, are affected strongly by the algorithm used, by the resolution of the images to which these algorithms are applied, and, at least for three of the algorithms (producing scale-dependent lacunarity estimates), by the scale at which the images are observed. Depending on the conditions under which the estimation of the lacunarity is carried out, lacunarity values range from 1.02 to 2.14 for the three systems tested, and all three of the systems used can be viewed alternatively as the most or the least "lacunar." Some of this indeterminacy and dependence on image resolution is alleviated in the averaged lacunarity estimates yielded by Chappard et al.'s algorithm. Further research will be needed to determine if these lacunarity estimates allow an improved, unique characterization of porous media.
URI: http://hdl.handle.net/10373/128
Appears in Collections:Science Engineering & Technology Collection

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