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Article: Ellipsoidal decision regions for motif-based patterned fabric defect detection

TitleEllipsoidal decision regions for motif-based patterned fabric defect detection
Authors
KeywordsDefect detection
Ellipsoidal decision region
Max-min decision region
Motif
Patterned fabric
Issue Date2010
PublisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/pr
Citation
Pattern Recognition, 2010, v. 43 n. 6, p. 2132-2144 How to Cite?
AbstractThis paper presents a study of using ellipsoidal decision regions for motif-based patterned fabric defect detection, the result of which is found to improve the original detection success using max-min decision region of the energy-variance values. In our previous research, max-min decision region was found to be effective in distinct cases but ill detect the ambiguous false-positive and false-negative cases. To alleviate this problem, we first assume that the energy-variance values can be described by a Gaussian mixture model. Second, we apply k-means clustering to roughly identify the various clusters that make up the entire data population. Third, convex hull of each cluster is employed as a basis for fitting an ellipsoidal decision region over it. Defect detection is then based on these ellipsoidal regions. To validate the method, three wallpaper groups are evaluated using the new ellipsoidal regions, and compared with those results obtained using the max-min decision region. For the p2 group, success rate improves from 93.43% to 100%. For the pmm group, success rate improves from 95.9% to 96.72%, while the p4 m group records the same success rate at 90.77%. This demonstrates the superiority of using ellipsoidal decision regions in motif-based defect detection. © 2009 Elsevier Ltd. All rights reserved.
Persistent Identifierhttp://hdl.handle.net/10722/73563
ISSN
2015 Impact Factor: 3.399
2015 SCImago Journal Rankings: 2.051
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorNgan, HYTen_HK
dc.contributor.authorPang, GKHen_HK
dc.contributor.authorYung, NHCen_HK
dc.date.accessioned2010-09-06T06:52:34Z-
dc.date.available2010-09-06T06:52:34Z-
dc.date.issued2010en_HK
dc.identifier.citationPattern Recognition, 2010, v. 43 n. 6, p. 2132-2144en_HK
dc.identifier.issn0031-3203en_HK
dc.identifier.urihttp://hdl.handle.net/10722/73563-
dc.description.abstractThis paper presents a study of using ellipsoidal decision regions for motif-based patterned fabric defect detection, the result of which is found to improve the original detection success using max-min decision region of the energy-variance values. In our previous research, max-min decision region was found to be effective in distinct cases but ill detect the ambiguous false-positive and false-negative cases. To alleviate this problem, we first assume that the energy-variance values can be described by a Gaussian mixture model. Second, we apply k-means clustering to roughly identify the various clusters that make up the entire data population. Third, convex hull of each cluster is employed as a basis for fitting an ellipsoidal decision region over it. Defect detection is then based on these ellipsoidal regions. To validate the method, three wallpaper groups are evaluated using the new ellipsoidal regions, and compared with those results obtained using the max-min decision region. For the p2 group, success rate improves from 93.43% to 100%. For the pmm group, success rate improves from 95.9% to 96.72%, while the p4 m group records the same success rate at 90.77%. This demonstrates the superiority of using ellipsoidal decision regions in motif-based defect detection. © 2009 Elsevier Ltd. All rights reserved.en_HK
dc.languageengen_HK
dc.publisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/pren_HK
dc.relation.ispartofPattern Recognitionen_HK
dc.subjectDefect detectionen_HK
dc.subjectEllipsoidal decision regionen_HK
dc.subjectMax-min decision regionen_HK
dc.subjectMotifen_HK
dc.subjectPatterned fabricen_HK
dc.titleEllipsoidal decision regions for motif-based patterned fabric defect detectionen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0031-3203&volume=43&issue=6&spage=2132&epage=2144&date=2009&atitle=Ellipsoidal+decision+regions+for+motif-based+patterned+fabric+defect+detectionen_HK
dc.identifier.emailPang, GKH:gpang@eee.hku.hken_HK
dc.identifier.emailYung, NHC:nyung@eee.hku.hken_HK
dc.identifier.authorityPang, GKH=rp00162en_HK
dc.identifier.authorityYung, NHC=rp00226en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.patcog.2009.12.001en_HK
dc.identifier.scopuseid_2-s2.0-76749157891en_HK
dc.identifier.hkuros168561en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-76749157891&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume43en_HK
dc.identifier.issue6en_HK
dc.identifier.spage2132en_HK
dc.identifier.epage2144en_HK
dc.identifier.isiWOS:000275987700011-
dc.publisher.placeNetherlandsen_HK
dc.identifier.scopusauthoridNgan, HYT=15078140700en_HK
dc.identifier.scopusauthoridPang, GKH=7103393283en_HK
dc.identifier.scopusauthoridYung, NHC=7003473369en_HK
dc.identifier.citeulike6481668-

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