Abstract
The study is concerned with putting forth a novel method of determination the pore size and its distribution for pores of different shapes. The identification of irregular and branched pores is associated with difficulties in their separation, as well as in the quantification of their size and shape characteristics. Recent developments in digital image processing provides a relatively new technology that allows visualization of the internal structure of objects. Our research was conducted using computer-aided tomography, and in turn, statistical techniques. This seems to be very useful in characterizing the pore volume distribution and in quantifying the differences in pore structures of the investigated materials. In this paper, the methodology is illustrated with a number of soil aggregates which differ in terms of soil fertilization. The approach is universal, and can be successfully applied for many tasks in data mining where pore characteristics are needed.
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References
Czachor, H., Lipiec, J.: The effects of manure application on soil aggregation. International Agrophysics 18, 217–223 (2004)
Dexter, A.R.: Advances in characterization of soil structure. Soil and Tillage Research 11, 198–238 (1988)
Papadopoulos, A., Bird, N.R., Whitmore, A.P., Mooney, S.J.: Investigating the effects of organic and conventional management on soil aggregate stability using X-ray computed tomography. European Journal of Soil Science 60, 360–388 (2009)
Peth, S., Nellesen, J., Fischer, G., Horn, R.: Non-invasive 3D analysis of local soil deformation under mechanical and hydraulic stresses by uCT and digital image correlation. Soil and Tillage Research 111, 3–18 (2010)
Nowak, P., Romaniuk, M.: Pricing and simulations of catastrophe bonds. Insurance: Mathematics and Economics 52, 18–28 (2013)
Swanepoel, C.J., Doku, W.O.: New goodness-of-fit tests for the error distribution of autoregressive time-series models. Computational Statistics and Data Analysis 43, 333–340 (2003)
Charytanowicz, M., Kulczycki, P.: Nonparametric Regression for Analyzing Correlation between Medical Parameters. In: Pietka, E., Kawa, J. (eds.) Information Technologies in Biomedicine. ASC, vol. 47, pp. 437–444. Springer, Heidelberg (2008)
Kulczycki, P., Charytanowicz, M.: Conditional Parameter Identification with Different Losses of Under- and Overestimation. Applied Mathematical Modelling 37, 2166–2177 (2013)
Silverman, B.W.: Density Estimation for Statistics and Data Analysis. Chapman and Hall, London (1986)
Lange, K.: Numerical Analysis for Statisticians. Statistics and Computing. Springer, New York (2000)
Kincaid, D., Cheney, W.: Numerical Analysis. Brooks/Cole, Pacific Grove (2002)
Zdravkov, B., Cermak, J., Sefara, M., Janku, J.: Pore classification in the characterization of porous materials: A perspective. Central European Journal of Chemistry 5, 385–395 (2007)
Król, A., Niewczas, J., Charytanowicz, M., Gonet, S., Lichner, L., Czachor, H., Lamorski, K.: Water-stable and non-stable soil aggregates and their pore size distributions. In: 20th International Poster Day and Institute of Hydrology Open Day: Transport of Water, Chemicals and Energy in the Soil – Plant – Atmosphere System, Bratislava, pp. 870–871 (2012)
Draper, N.R., Smith, H.: Applied regression analysis. John Wiley and Sons, New York (1981)
Pratt, W.K.: Digital Image Processing. John Wiley and Sons, New York (2001)
Aphelion 4.0.10 user guide: ADCIS S.A. (1997)
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Charytanowicz, M. (2014). An Algorithm for the Pore Size Determination Using Digital Image Analysis. In: Piętka, E., Kawa, J., Wieclawek, W. (eds) Information Technologies in Biomedicine, Volume 3. Advances in Intelligent Systems and Computing, vol 283. Springer, Cham. https://doi.org/10.1007/978-3-319-06593-9_20
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DOI: https://doi.org/10.1007/978-3-319-06593-9_20
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-06592-2
Online ISBN: 978-3-319-06593-9
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