DocumentCode :
3482388
Title :
Optimal textural features for flaw detection in textile materials
Author :
Bodnarova, Adriana ; Williams, John A. ; Bennamoun, Mohammed ; Kubik, Kurt K.
Author_Institution :
Space Centre of Satellite Navigation, Queensland Univ. of Technol., Brisbane, Qld., Australia
Volume :
1
fYear :
1997
fDate :
4-4 Dec. 1997
Firstpage :
307
Abstract :
This paper examines the problem of quality control and defect identification in woven textile fabrics by introducing an improved method for texture description. The approach is based on spatial gray level dependence methodology and addresses the issue of optimal parameter selection for deriving the maximum textural information. We introduce the use of the χ2 significance test on elemental feature matrices in order to obtain higher per feature texture description and hence improve the capture of defects in the underlying textile pattern.
Keywords :
fibres; flaw detection; image texture; matrix algebra; optimisation; parameter estimation; quality control; statistical analysis; textile industry; χ2 significance test; defect identification; elemental feature matrices; flaw detection; maximum textural information; optimal parameter selection; optimal textural features; quality control; spatial gray level dependence; statistical approach; textile materials; textile pattern defects; texture description; woven textile fabrics; Computer vision; Costs; Fabrics; Image texture analysis; Manufacturing; Production; Quality control; Space technology; Testing; Textiles;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
TENCON '97. IEEE Region 10 Annual Conference. Speech and Image Technologies for Computing and Telecommunications., Proceedings of IEEE
Conference_Location :
Brisbane, Qld., Australia
Print_ISBN :
0-7803-4365-4
Type :
conf
DOI :
10.1109/TENCON.1997.647318
Filename :
647318
Link To Document :
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