DocumentCode :
498867
Title :
The detection for fabric defect based on two-dimensional orthogonal wavelet
Author :
Jiang, Hui Yu ; Dong, Min ; Li, We
Author_Institution :
Inst. of Chem. Eng., Wuhan Univ. of Sci. & Eng., Wuhan, China
Volume :
4
fYear :
2009
fDate :
12-15 July 2009
Firstpage :
2470
Lastpage :
2472
Abstract :
In this paper, the method of orthogonal wavelet transform was used to decompose monolayer from fabric image. And the sub-images of horizontal and vertical direction are extracted to represent respectively the textures of fabric in warp and weft. Then, energy in warp and weft; variance, entropy and range of eigenvalue is calculated. And they were also compared to the normal control to determine whether there is any defect exists. Meanwhile, some typical defect forms of plain weave white cotton fabric has been detection in this paper. The experiment results show that the method is effective and feasible.
Keywords :
eigenvalues and eigenfunctions; fabrics; feature extraction; image texture; mechanical engineering computing; wavelet transforms; weaving; eigenvalue; entropy; fabric defect detection; fabric image; feature extraction; image texture; monolayer decomposition; plain weave white cotton fabric; two-dimensional orthogonal wavelet transform; Cybernetics; Fabrics; Machine learning; Defect; Detection; Fabric; Orthogonal Decomposition; Wavelet Transform;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics, 2009 International Conference on
Conference_Location :
Baoding
Print_ISBN :
978-1-4244-3702-3
Electronic_ISBN :
978-1-4244-3703-0
Type :
conf
DOI :
10.1109/ICMLC.2009.5212235
Filename :
5212235
Link To Document :
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