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Article: Fabric defect detection by Fourier analysis

TitleFabric defect detection by Fourier analysis
Authors
Issue Date2000
PublisherIEEE.
Citation
IEEE Transactions on Industry Applications, 2000, v. 36 n. 5, p. 1267-1276 How to Cite?
AbstractMany fabric defects are very small and undistinguishable, which makes them very difficult to detect by only monitoring the intensity change. Faultless fabric is a repetitive and regular global texture and Fourier transforms can be applied to monitor the spatial frequency spectrum of a fabric. When a defect occurs in fabric, its regular structure is changed so that the corresponding intensity at some specific positions of the frequency spectrum would change. However, the three-dimensional frequency spectrum is very difficult to analyze. In this paper, a simulated fabric model is used to understand the relationship between the fabric structure in the image space and in the frequency space. Based on the three-dimensional frequency spectrum, two significant spectral diagrams are defined and used for analyzing the fabric defect. These two diagrams are called the central spatial frequency spectrums. The defects are broadly classified into four classes: (1) double yarn; (2) missing yarn; (3) webs or broken fabric; and (4) yarn densities variation. After evaluating these four classes of defects using some simulated models and real samples, seven characteristic parameters for a central spatial frequency spectrum are extracted for defect classification.
Persistent Identifierhttp://hdl.handle.net/10722/42882
ISSN
2015 Impact Factor: 1.901
2015 SCImago Journal Rankings: 1.388

 

DC FieldValueLanguage
dc.contributor.authorChan, CHen_HK
dc.contributor.authorPang, GKHen_HK
dc.date.accessioned2007-03-23T04:33:59Z-
dc.date.available2007-03-23T04:33:59Z-
dc.date.issued2000en_HK
dc.identifier.citationIEEE Transactions on Industry Applications, 2000, v. 36 n. 5, p. 1267-1276en_HK
dc.identifier.issn0093-9994en_HK
dc.identifier.urihttp://hdl.handle.net/10722/42882-
dc.description.abstractMany fabric defects are very small and undistinguishable, which makes them very difficult to detect by only monitoring the intensity change. Faultless fabric is a repetitive and regular global texture and Fourier transforms can be applied to monitor the spatial frequency spectrum of a fabric. When a defect occurs in fabric, its regular structure is changed so that the corresponding intensity at some specific positions of the frequency spectrum would change. However, the three-dimensional frequency spectrum is very difficult to analyze. In this paper, a simulated fabric model is used to understand the relationship between the fabric structure in the image space and in the frequency space. Based on the three-dimensional frequency spectrum, two significant spectral diagrams are defined and used for analyzing the fabric defect. These two diagrams are called the central spatial frequency spectrums. The defects are broadly classified into four classes: (1) double yarn; (2) missing yarn; (3) webs or broken fabric; and (4) yarn densities variation. After evaluating these four classes of defects using some simulated models and real samples, seven characteristic parameters for a central spatial frequency spectrum are extracted for defect classification.en_HK
dc.format.extent1579210 bytes-
dc.format.extent28160 bytes-
dc.format.extent961133 bytes-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypeapplication/msword-
dc.format.mimetypeapplication/pdf-
dc.languageengen_HK
dc.publisherIEEE.en_HK
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.rights©2000 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.en_HK
dc.titleFabric defect detection by Fourier analysisen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0093-9994&volume=36&issue=5&spage=1267&epage=1276&date=2000&atitle=Fabric+defect+detection+by+Fourier+analysisen_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.doi10.1109/28.871274en_HK
dc.identifier.scopuseid_2-s2.0-0034270046-
dc.identifier.hkuros61147-
dc.identifier.citeulike6013851-

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