MULTISCALE ROUGHNESS ANALYSIS OF PARTICLES: APPLICATION TO THE CLASSIFICATION OF DETRITAL SEDIMENTS

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dc.contributor.author Drolon H.
dc.contributor.author Hoyez B.
dc.contributor.author Druaux F.
dc.contributor.author Faure A.
dc.date.accessioned 2022-01-31T06:18:48Z
dc.date.available 2022-01-31T06:18:48Z
dc.date.issued 2003
dc.identifier https://elibrary.ru/item.asp?id=5212855
dc.identifier.citation Mathematical Geology, 2003, 35, 7, 805-817
dc.identifier.issn 0882-8121
dc.identifier.uri https://repository.geologyscience.ru/handle/123456789/34736
dc.description.abstract The shape of detrital quartz grains, mainly acquired under the effect of mechanical transport agents, has been observed and described for a long time by sedimentologists. The roughness of these grains is recognized as an important parameter for analyzing sediments, but to quantify this parameter with a discriminant measure can be difficult. By using the concept of multiresolution analysis and the wavelet formalism, we develop a roughness descriptor for particles, possessing multiscale analysis capabilities. It allows analyses of wear and erosion phenomena acting on particles by decomposing the information on the shape into different resolution levels, each level corresponding to a different scale. Thus it becomes possible to differentiate coarse roughness from finer roughness of a grain's outline. This descriptor is invariant under affine geometric transformation and can therefore be used to compare sands stemming from a wide range of natural environments. An application to the analysis and the classification of detrital sediments, along with a comparison with Fourier and fractal grain shape analysis, illustrates the performance of the method.
dc.subject GRAIN SHAPE ANALYSIS
dc.subject ROUGHNESS ANALYSIS
dc.subject WAVELET TRANSFORM
dc.subject CLASSIFICATION
dc.subject NEURAL NETWORKS
dc.title MULTISCALE ROUGHNESS ANALYSIS OF PARTICLES: APPLICATION TO THE CLASSIFICATION OF DETRITAL SEDIMENTS
dc.type Статья


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