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Article: Fabric defect segmentation using multichannel blob detectors

TitleFabric defect segmentation using multichannel blob detectors
Authors
KeywordsDefect detection
Gabor filters
Multichannel filtering
Textile industry
Quality assurance
Issue Date2000
PublisherS P I E - International Society for Optical Engineering. The Journal's web site is located at http://www.spie.org/oe
Citation
Optical Engineering, 2000, v. 39 n. 12, p. 3176-3190 How to Cite?
AbstractThe problem of automated defect detection in textured materials is investigated. A new algorithm based on multichannel filtering is presented. The texture features are extracted by filtering the acquired image using a filter bank consisting of a number of real Gabor functions, with multiple narrow spatial frequency and orientation channels. For each image, we propose the use of image fusion to multiplex the information from sixteen different channels obtained in four orientations. Adaptive degrees of thresholding and the associated effect on sensitivity to material impurities are discussed. This algorithm realizes large computational savings over the previous approaches and enables high-quality real-time defect detection. The performance of this algorithm has been tested thoroughly on real fabric defects, and experimental results have confirmed the usefulness of the approach.
Persistent Identifierhttp://hdl.handle.net/10722/42112
ISSN
2023 Impact Factor: 1.1
2023 SCImago Journal Rankings: 0.331
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorKumar, Aen_HK
dc.contributor.authorPang, Gen_HK
dc.date.accessioned2007-01-08T02:29:14Z-
dc.date.available2007-01-08T02:29:14Z-
dc.date.issued2000en_HK
dc.identifier.citationOptical Engineering, 2000, v. 39 n. 12, p. 3176-3190en_HK
dc.identifier.issn0091-3286en_HK
dc.identifier.urihttp://hdl.handle.net/10722/42112-
dc.description.abstractThe problem of automated defect detection in textured materials is investigated. A new algorithm based on multichannel filtering is presented. The texture features are extracted by filtering the acquired image using a filter bank consisting of a number of real Gabor functions, with multiple narrow spatial frequency and orientation channels. For each image, we propose the use of image fusion to multiplex the information from sixteen different channels obtained in four orientations. Adaptive degrees of thresholding and the associated effect on sensitivity to material impurities are discussed. This algorithm realizes large computational savings over the previous approaches and enables high-quality real-time defect detection. The performance of this algorithm has been tested thoroughly on real fabric defects, and experimental results have confirmed the usefulness of the approach.en_HK
dc.format.extent478996 bytes-
dc.format.extent4125 bytes-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypetext/plain-
dc.languageengen_HK
dc.publisherS P I E - International Society for Optical Engineering. The Journal's web site is located at http://www.spie.org/oeen_HK
dc.relation.ispartofOptical Engineeringen_HK
dc.rightsCopyright 2000 Society of Photo‑Optical Instrumentation Engineers (SPIE). One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this publication for a fee or for commercial purposes, and modification of the contents of the publication are prohibited. This article is available online at https://doi.org/10.1117/1.1327837-
dc.subjectDefect detectionen_HK
dc.subjectGabor filtersen_HK
dc.subjectMultichannel filteringen_HK
dc.subjectTextile industryen_HK
dc.subjectQuality assuranceen_HK
dc.titleFabric defect segmentation using multichannel blob detectorsen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0091-3286&volume=39&issue=12&spage=3176&epage=3190&date=2000&atitle=Fabric+defect+segmentation+using+multichannel+blob+detectorsen_HK
dc.identifier.emailPang, G:gpang@eee.hku.hken_HK
dc.identifier.authorityPang, G=rp00162en_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.doi10.1117/1.1327837en_HK
dc.identifier.scopuseid_2-s2.0-0034430283en_HK
dc.identifier.hkuros62075-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-0034430283&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume39en_HK
dc.identifier.issue12en_HK
dc.identifier.spage3176en_HK
dc.identifier.epage3190en_HK
dc.identifier.isiWOS:000166413000008-
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridKumar, A=35198218300en_HK
dc.identifier.scopusauthoridPang, G=7103393283en_HK
dc.identifier.issnl0091-3286-

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