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Stochastic texture image estimators for local spatial anisotropy and its variability

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Stochastic texture image estimators for local spatial anisotropy and its variability

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Título Stochastic texture image estimators for local spatial anisotropy and its variability
Autor Scharcanski, Jacob
Dodson, C.T.J.
Abstract A new image analysis technique is proposed for the evaluation of local anisotropy and its variability in stochastic texture images. It utilizes the gradient function to provide information on local anisotropy, from two-dimensional (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, and show that the proposed technique is more robust to unfavorable imaging conditions than other approaches. 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.
Contido em IEEE transactions on instrumentation and measurement. New York. Vol. 49, n. 5 (oct. 2000), p. 971-979
Assunto Automação industrial
Processamento : Fibras
Reconhecimento : Padroes
[en] Anisotropy
[en] Density variability
[en] Machine control
[en] Monitoring
[en] Stochastic structures
[en] Texture image analysis
Origem Estrangeiro
Tipo Artigo de periódico
URI http://hdl.handle.net/10183/27557
Arquivos Descrição Formato
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