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Analysis of texture can yield information about the rock's source material, conditions and environment of deposition (for sedimentary rock) or crystallization and recrystallization (for igneous and metamorphic rock, respectively), and subsequent geologic history and change.
In this article, we investigate the problem of the analysis of multispectral image textures allowing a joint spectral and spatial analysis of texture.
The analysis of texture suggests random distribution of the orientations of ferrite grains, as a consequence of the process of production, which includes solidification followed by phase transformation.
Especially, the analysis of texture gradients in bulk materials using neutron diffraction has advantages over laboratory X-rays and EBSD for many scientific cases.
The process parameters identified by the classifier are fine-tuned using a gradient optimization algorithm driven by continuum sensitivity analysis of texture evolution.
It was shown that the analysis of texture evolution during deformation and annealing can be used as an effective tool to optimize cold rolling degree and annealing conditions.
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A statistical model is proposed for analysis of the texture of land cover types for global and regional land cover classification by using texture features extracted by multiresolution image analysis techniques.
Pinpointing the exact depositional setting for an ancient carbonate deposit requires detailed analysis of its texture, composition, sedimentary structures, geometry, fossil content, and stratigraphic relationships with modern carbonate depositional sites.
The trainable filter banks make an excellent tool in the analysis of repetitive texture patterns.
Analysis of image texture demonstrated that Haralick feature 4 was the most suitable for discriminating stroma from PCa.
At each transect point additional soil samples were taken for analysis of soil texture, standard soil properties and electrolytic conductivity.
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Justyna Jupowicz-Kozak
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