Jochen Düll

Evangelische Hochschule Darmstadt, Darmstadt, Hesse, Germany

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Publications (3)2.61 Total impact

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    ABSTRACT: b Estimation of the probability of finite percolation in porous microstructures from tomographic images Percolation is an important property of porous media, as it describes the connectivity of pores. We propose a novel, direction-dependent percolation probability which can be efficiently estimated from three-dimensional images ob-tained by microtomography. Furthermore, in order to describe the penetrability of the pore space by particles of a given diameter or a fluid of a given surface tension, we introduce a percolation probability depending on the width of the pores, from which we may also derive a measure of the mean pore channel width. As application examples, we consider the penetrability of porous beryllium pebbles, the connectivity of pores in arctic firn, the percolation of the pore space of aluminum foams and the mean width of the percolating space between the fibers in a laminate's perco-lating pore space.
    International Journal of Materials Research (formerly Zeitschrift fuer Metallkunde) 02/2012; 103(2):184-191. DOI:10.3139/146.110669 · 0.64 Impact Factor
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    Markus Kautz · Jochen Düll · Joachim Ohser ·
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    ABSTRACT: A large spatio-temporal data set monitoring the annual progress of bark beetle infestation in the Bavarian Forest National Park (Germany) is statistically analysed by means of complex image analysis algorithms. The infestation data were obtained by color-infrared (CIR) aerial image interpretation and cover 10 subsequent years (2001–2010). Newly emerged infestation patches are hypothesized as spatially correlated to locations of previous year’s infestation. Both areas, source patches and subsequently emerged patches, are considered as two disjoint random sets. Their spatio-temporal dependence is analysed by two methods: the classical approach based on the measurement of cross-covariance functions, and a second one based on nearest neighbor distances. The resulting characteristics can be interpreted as pre-disposition probabilities of bark beetle infestation depending on distance to sources. Both methods show a strong short-range preference, which decreases with increasing distances.
    Image Analysis and Stereology 11/2011; 30(3):123-131. DOI:10.5566/ias.v30.p123-131 · 0.97 Impact Factor
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    ABSTRACT: In this work, we analyzed the color and texture of irises, ocular prostheses, and cosmetic colored contact lenses measured by means of a multispectral system, which provides the CIE L*a*b* colorimetric coordinates of a high resolution image pixel by pixel. The same subject, who has dark brown irises, participated in the measurement of all the contact lenses. The CIE L*a*b* colorimetric coordinates were analyzed to classify the samples into three major groups (brown, blue and green) using a new algorithm developed for this purpose. This classification allowed us to carry out a comparison of the color associated with each set of samples, using the corresponding color gamuts in the CIE L*a*b* color space. Furthermore, we analyzed the iris color reproduction achieved by prostheses and contact lenses in terms of CIEDE2000 color differences, and obtained closer results with prostheses. In addition, we performed an analysis of texture by means of the color spatial distribution of all samples. This was achieved by means of two statistical approaches: first order statistics of image histograms and second order statistics using co-occurrence matrices. The results suggest that the texture associated with real irises, ocular prostheses and colored contact lenses is very different. This study provides useful information about the color and texture of irises that may help to establish a strategy for improving the techniques used in the manufacturing process of prostheses and colored contact lenses to obtain a better and more realistic appearance. © 2010 Wiley Periodicals, Inc. Col Res Appl, 2011
    Color Research & Application 10/2011; 36(5):373 - 382. DOI:10.1002/col.20635 · 1.00 Impact Factor