Stochastic texture image estimators for local spatial anisotropy and its variability

Author

Scharcanski, J. ; Dodson, C.T.J.

Author_Institution

Inst. of Inf., Univ. Fed. do Rio Grande do Sul, Porto Alegre, Brazil

Volume

49

Issue

5

fYear

2000

fDate

10/1/2000 12:00:00 AM

Firstpage

971

Lastpage

979

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

Keywords

image recognition; image texture; industrial control; paper; paper industry; stochastic systems; 2D density images; continuous manufacturing processes; control of anisotropy; foil materials; image analysis; image estimators; light transmission; local density; local spatial anisotropy; machine control; monitoring; nonwoven textiles; on-line application; paper; polymer sheets; radiography; stochastic texture images; texture analysis; variability; Anisotropic magnetoresistance; Image texture analysis; Manufacturing processes; Polymers; Radiography; Robustness; Sheet materials; Stochastic processes; Textiles; Two dimensional displays;

fLanguage

English

Journal_Title

Instrumentation and Measurement, IEEE Transactions on

Publisher

ieee

ISSN

0018-9456

Type

jour

DOI

10.1109/19.872916

Filename

872916