Stochastic texture image estimators for local spatial anisotropy and its variability

dc.creatorScharcanski, Jacob
dc.creatorDodson, C.T.J.
dc.date2011-01-28T05:59:02Z
dc.date2000
dc.identifier0018-9456
dc.identifierhttp://hdl.handle.net/10183/27557
dc.identifier000282352
dc.descriptionA 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.
dc.formatapplication/pdf
dc.languageeng
dc.relationIEEE transactions on instrumentation and measurement. New York. Vol. 49, n. 5 (oct. 2000), p. 971-979
dc.rightsOpen Access
dc.subjectAutomação industrial
dc.subjectProcessamento : Fibras
dc.subjectReconhecimento : Padroes
dc.subjectAnisotropy
dc.subjectDensity variability
dc.subjectMachine control
dc.subjectMonitoring
dc.subjectStochastic structures
dc.subjectTexture image analysis
dc.titleStochastic texture image estimators for local spatial anisotropy and its variability
dc.typeArtigo de periódico
dc.typeEstrangeiro


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