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Particulate material fabric characterization by rotational haar wavelet transform
AbstractA Rotational Haar Wavelet Transform (RHWT) method is developed to characterize the fabric of particulate assemblies from two-dimensional images. A Maximum Energy Ratio Ψ reveals the fabric direction and its intensity. The method is implemented on 12 sand and 3 rice specimens of various shapes. It was shown that Ψ may be expressed in terms of a material's aspect ratio and relative density. A material fabric classification system based on Ψ is proposed. The parameter also defines the fabric tensor for cross anisotropic material. Scanning electron microscope images of kaolinite clay and several rock images are also analyzed.
Particulate material fabric characterization by rotational haar wavelet transform
AbstractA Rotational Haar Wavelet Transform (RHWT) method is developed to characterize the fabric of particulate assemblies from two-dimensional images. A Maximum Energy Ratio Ψ reveals the fabric direction and its intensity. The method is implemented on 12 sand and 3 rice specimens of various shapes. It was shown that Ψ may be expressed in terms of a material's aspect ratio and relative density. A material fabric classification system based on Ψ is proposed. The parameter also defines the fabric tensor for cross anisotropic material. Scanning electron microscope images of kaolinite clay and several rock images are also analyzed.
Particulate material fabric characterization by rotational haar wavelet transform
Zheng, Junxing (author) / Hryciw, Roman D. (author)
Computers and Geotechnics ; 88 ; 46-60
2017-02-28
15 pages
Article (Journal)
Electronic Resource
English
Particulate material fabric characterization by rotational haar wavelet transform
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