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Conference Paper: A real-time computer vision system for detecting defects in textile fabrics

TitleA real-time computer vision system for detecting defects in textile fabrics
Authors
KeywordsComputer vision
Defect detection
Fabrics
Filter selection
Gabor filter
Issue Date2005
PublisherIEEE.
Citation
Proceedings Of The Ieee International Conference On Industrial Technology, 2005, v. 2005, p. 469-474 How to Cite?
AbstractThis paper proposes a real-time computer vision system for detecting defects in textile fabrics. The developments of both the hardware and software platforms are presented. The design of the prototyped defect detection system ensures that the fabric moves smoothly and evenly so that high quality images can be captured. The paper also proposes a new filter selection method to detect fabric defects, which can automatically tune the Gabor functions to match with the texture information. The filter selection method is further developed into a new defect segmentation algorithm. The scheme is tested both on-line and off-line by using a variety of homogeneous textile images with different defects. The results exhibit accurate defect detection with low false alarm, thus confirming the robustness and effectiveness of the proposed system. © 2005 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/46561
References

 

DC FieldValueLanguage
dc.contributor.authorMak, KLen_HK
dc.contributor.authorPeng, Pen_HK
dc.contributor.authorLau, HYKen_HK
dc.date.accessioned2007-10-30T06:52:58Z-
dc.date.available2007-10-30T06:52:58Z-
dc.date.issued2005en_HK
dc.identifier.citationProceedings Of The Ieee International Conference On Industrial Technology, 2005, v. 2005, p. 469-474en_HK
dc.identifier.urihttp://hdl.handle.net/10722/46561-
dc.description.abstractThis paper proposes a real-time computer vision system for detecting defects in textile fabrics. The developments of both the hardware and software platforms are presented. The design of the prototyped defect detection system ensures that the fabric moves smoothly and evenly so that high quality images can be captured. The paper also proposes a new filter selection method to detect fabric defects, which can automatically tune the Gabor functions to match with the texture information. The filter selection method is further developed into a new defect segmentation algorithm. The scheme is tested both on-line and off-line by using a variety of homogeneous textile images with different defects. The results exhibit accurate defect detection with low false alarm, thus confirming the robustness and effectiveness of the proposed system. © 2005 IEEE.en_HK
dc.format.extent4788341 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.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.-
dc.subjectComputer visionen_HK
dc.subjectDefect detectionen_HK
dc.subjectFabricsen_HK
dc.subjectFilter selectionen_HK
dc.subjectGabor filteren_HK
dc.titleA real-time computer vision system for detecting defects in textile fabricsen_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.2005.1600684en_HK
dc.identifier.scopuseid_2-s2.0-33847337390en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-33847337390&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume2005en_HK
dc.identifier.spage469en_HK
dc.identifier.epage474en_HK
dc.identifier.scopusauthoridMak, KL=7102680226en_HK
dc.identifier.scopusauthoridPeng, P=7102844225en_HK
dc.identifier.scopusauthoridLau, HYK=7201497761en_HK

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