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- Publisher Website: 10.1016/j.imavis.2009.03.007
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Article: Fabric defect detection using morphological filters
Title | Fabric defect detection using morphological filters | ||||
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Authors | |||||
Keywords | Defect Detection Gabor Wavelet Network Morphological Filter Quality Control Textile Fabrics | ||||
Issue Date | 2009 | ||||
Publisher | Elsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/imavis | ||||
Citation | Image And Vision Computing, 2009, v. 27 n. 10, p. 1585-1592 How to Cite? | ||||
Abstract | In this paper, a novel defect detection scheme based on morphological filters is proposed to tackle the problem of automated defect detection for woven fabrics. In the proposed scheme, important texture features of the textile fabric are extracted using a pre-trained Gabor wavelet network. These texture features are then used to facilitate the construction of structuring elements in subsequent morphological processing to remove the fabric background and isolate the defects. Since the proposed defect detection scheme requires a few morphological filters only, the amount of computational load involved is not significant. The performance of the proposed scheme is evaluated by using a wide variety of homogeneous textile images with different types of common fabric defects. The test results obtained exhibit accurate defect detection with low false alarms, thus showing the effectiveness and robustness of the proposed detection scheme. In addition, the proposed detection scheme is further evaluated in real time by using a prototyped automated inspection system. © 2009 Elsevier B.V. All rights reserved. | ||||
Persistent Identifier | http://hdl.handle.net/10722/155917 | ||||
ISSN | 2023 Impact Factor: 4.2 2023 SCImago Journal Rankings: 1.204 | ||||
ISI Accession Number ID |
Funding Information: The work described in this paper was supported by a grant from the research Grants Council of the Hong Kong Special Administrative Region, China (Project No. HKU7382/02E). The authors would also like to thank the reviewers for their helpful suggestions and constructive comments on the earlier versions of the paper. | ||||
References |
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Mak, KL | en_US |
dc.contributor.author | Peng, P | en_US |
dc.contributor.author | Yiu, KFC | en_US |
dc.date.accessioned | 2012-08-08T08:38:23Z | - |
dc.date.available | 2012-08-08T08:38:23Z | - |
dc.date.issued | 2009 | en_US |
dc.identifier.citation | Image And Vision Computing, 2009, v. 27 n. 10, p. 1585-1592 | en_US |
dc.identifier.issn | 0262-8856 | en_US |
dc.identifier.uri | http://hdl.handle.net/10722/155917 | - |
dc.description.abstract | In this paper, a novel defect detection scheme based on morphological filters is proposed to tackle the problem of automated defect detection for woven fabrics. In the proposed scheme, important texture features of the textile fabric are extracted using a pre-trained Gabor wavelet network. These texture features are then used to facilitate the construction of structuring elements in subsequent morphological processing to remove the fabric background and isolate the defects. Since the proposed defect detection scheme requires a few morphological filters only, the amount of computational load involved is not significant. The performance of the proposed scheme is evaluated by using a wide variety of homogeneous textile images with different types of common fabric defects. The test results obtained exhibit accurate defect detection with low false alarms, thus showing the effectiveness and robustness of the proposed detection scheme. In addition, the proposed detection scheme is further evaluated in real time by using a prototyped automated inspection system. © 2009 Elsevier B.V. All rights reserved. | en_US |
dc.language | eng | en_US |
dc.publisher | Elsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/imavis | en_US |
dc.relation.ispartof | Image and Vision Computing | en_US |
dc.subject | Defect Detection | en_US |
dc.subject | Gabor Wavelet Network | en_US |
dc.subject | Morphological Filter | en_US |
dc.subject | Quality Control | en_US |
dc.subject | Textile Fabrics | en_US |
dc.title | Fabric defect detection using morphological filters | en_US |
dc.type | Article | en_US |
dc.identifier.email | Mak, KL:makkl@hkucc.hku.hk | en_US |
dc.identifier.email | Yiu, KFC:cedric@hkucc.hku.hk | en_US |
dc.identifier.authority | Mak, KL=rp00154 | en_US |
dc.identifier.authority | Yiu, KFC=rp00206 | en_US |
dc.description.nature | link_to_subscribed_fulltext | en_US |
dc.identifier.doi | 10.1016/j.imavis.2009.03.007 | en_US |
dc.identifier.scopus | eid_2-s2.0-67349127629 | en_US |
dc.relation.references | http://www.scopus.com/mlt/select.url?eid=2-s2.0-67349127629&selection=ref&src=s&origin=recordpage | en_US |
dc.identifier.volume | 27 | en_US |
dc.identifier.issue | 10 | en_US |
dc.identifier.spage | 1585 | en_US |
dc.identifier.epage | 1592 | en_US |
dc.identifier.eissn | 1872-8138 | - |
dc.identifier.isi | WOS:000268403800015 | - |
dc.publisher.place | Netherlands | en_US |
dc.identifier.scopusauthorid | Mak, KL=7102680226 | en_US |
dc.identifier.scopusauthorid | Peng, P=7102844225 | en_US |
dc.identifier.scopusauthorid | Yiu, KFC=24802813000 | en_US |
dc.identifier.citeulike | 4810925 | - |
dc.identifier.issnl | 0262-8856 | - |