Texture analysis for estimating spatial variability and anisotropy in planar stochastic structures
Some operators from the theory of texture image analysis are used to obtain a new method for the evaluation of anisotropy in planar stochastic structures. A local gradient function provides information on local anisotropy and its variability, from 2-D density images for foil materials like polymer s...
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| Published in | Optical Engineering Vol. 35; no. 8; pp. 2302 - 2309 |
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| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
01.08.1996
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| Online Access | Get full text |
| ISSN | 0091-3286 1560-2303 |
| DOI | 10.1117/1.600804 |
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| Abstract | Some operators from the theory of texture image analysis are used to obtain a new method for the evaluation of anisotropy in planar stochastic structures. A local gradient function provides information on local anisotropy and its variability, from 2-D density images for foil materials like polymer sheets, nonwoven textiles and paper. Such images can be captured by radiography or light transmission; results are reported for a range of paper structures. The method has potential for on-line application to monitoring and control of anisotropy and its variability, as well as local density itself, in continuous manufacturing processes. © |
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| AbstractList | Some operators from the theory of texture image analysis are used to obtain a new method for the evaluation of anisotropy in planar stochastic structures. A local gradient function provides information on local anisotropy and its variability, from 2-D density images for foil materials like polymer sheets, nonwoven textiles and paper. Such images can be captured by radiography or light transmission; results are reported for a range of paper structures. The method has potential for on-line application to monitoring and control of anisotropy and its variability, as well as local density itself, in continuous manufacturing processes. © |
| Author | Dodson, C. T. J Scharcanski, Jacob |
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| Title | Texture analysis for estimating spatial variability and anisotropy in planar stochastic structures |
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