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Conference Paper: Optimal morphological filter design for fabric defect detection

TitleOptimal morphological filter design for fabric defect detection
Authors
KeywordsDefect detection
Fabrics
Gabor wavelet networks
Mechatronics
Morphological filters
Issue Date2005
PublisherIEEE.
Citation
Proceedings Of The Ieee International Conference On Industrial Technology, 2005, v. 2005, p. 799-804 How to Cite?
AbstractThis paper investigates the problem of automated defect detection for textile fabrics and proposes a new optimal morphological filter design method for solving this problem. Gabor Wavelet Network (GWN) is adopted as a major technique to extract the texture features of textile fabrics. An optimal morphological filter can be constructed based on the texture features extracted. In view of this optimal filter, a new semi-supervised segmentation algorithm is then proposed. The performance of the scheme is evaluated by using a variety of homogeneous textile images with different types of common defects. The test results exhibit accurate defect detection with low false alarm, thus confirming the robustness and effectiveness of the proposed scheme. In addition, it can be shown that the algorithm proposed in this paper is suitable for on-line applications. Indeed, the proposed algorithm is a low cost PC based solution to the problem of defect detection for textile fabrics. © 2005 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/46562
References

 

DC FieldValueLanguage
dc.contributor.authorMak, KLen_HK
dc.contributor.authorPeng, Pen_HK
dc.contributor.authorLau, HYKen_HK
dc.date.accessioned2007-10-30T06:53:00Z-
dc.date.available2007-10-30T06:53:00Z-
dc.date.issued2005en_HK
dc.identifier.citationProceedings Of The Ieee International Conference On Industrial Technology, 2005, v. 2005, p. 799-804en_HK
dc.identifier.urihttp://hdl.handle.net/10722/46562-
dc.description.abstractThis paper investigates the problem of automated defect detection for textile fabrics and proposes a new optimal morphological filter design method for solving this problem. Gabor Wavelet Network (GWN) is adopted as a major technique to extract the texture features of textile fabrics. An optimal morphological filter can be constructed based on the texture features extracted. In view of this optimal filter, a new semi-supervised segmentation algorithm is then proposed. The performance of the scheme is evaluated by using a variety of homogeneous textile images with different types of common defects. The test results exhibit accurate defect detection with low false alarm, thus confirming the robustness and effectiveness of the proposed scheme. In addition, it can be shown that the algorithm proposed in this paper is suitable for on-line applications. Indeed, the proposed algorithm is a low cost PC based solution to the problem of defect detection for textile fabrics. © 2005 IEEE.en_HK
dc.format.extent4780724 bytes-
dc.format.extent2836 bytes-
dc.format.extent2656 bytes-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypetext/plain-
dc.format.mimetypetext/plain-
dc.languageengen_HK
dc.publisherIEEE.en_HK
dc.relation.ispartofProceedings of the IEEE International Conference on Industrial Technologyen_HK
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.rights©2005 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.subjectDefect detectionen_HK
dc.subjectFabricsen_HK
dc.subjectGabor wavelet networksen_HK
dc.subjectMechatronicsen_HK
dc.subjectMorphological filtersen_HK
dc.titleOptimal morphological filter design for fabric defect detectionen_HK
dc.typeConference_Paperen_HK
dc.identifier.emailMak, KL:makkl@hkucc.hku.hken_HK
dc.identifier.emailLau, HYK:hyklau@hkucc.hku.hken_HK
dc.identifier.authorityMak, KL=rp00154en_HK
dc.identifier.authorityLau, HYK=rp00137en_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.doi10.1109/ICIT.2005.1600745en_HK
dc.identifier.scopuseid_2-s2.0-33847287331en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-33847287331&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume2005en_HK
dc.identifier.spage799en_HK
dc.identifier.epage804en_HK
dc.identifier.scopusauthoridMak, KL=7102680226en_HK
dc.identifier.scopusauthoridPeng, P=7102844225en_HK
dc.identifier.scopusauthoridLau, HYK=7201497761en_HK
dc.identifier.citeulike6013869-

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