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Article: Discriminative fabric defect detection using adaptive wavelets

TitleDiscriminative fabric defect detection using adaptive wavelets
Authors
KeywordsAdaptive wavelets
Defect detection
Discriminative feature extraction
Undecimated discrete wavelet transform
Issue Date2002
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, 2002, v. 41 n. 12, p. 3116-3126 How to Cite?
AbstractWe propose a new method for fabric defect detection by incorporating the design of an adaptive wavelet-based feature extractor with the design of an Euclidean distance-based detector. The proposed method characterizes the fabric image with multiscale wavelet features by using undecimated discrete wavelet transforms. Each nonoverlapping window of the fabric image is then detected as defect or nondefect with an Euclidean distance-based detector. Instead of using the standard wavelet bases, an adaptive wavelet basis is designed for the detection of fabric defects. Minimization of the detection error Is achieved by incorporating the design of the adaptive wavelet with the design of the detector parameters using a discriminative feature extraction (DFE) training method. The proposed method has been evaluated on 480 defect samples from five types of defects, and 480 nondefect samples, where a 97.5% detection rate and 0.63% false alarm rate were achieved. The evaluations were also carried out on unknown types of defects, where a 93.3% detection rate and 3.97% false alarm rate were achieved in the detection of 180 defect samples and 780 nondefect samples. © 2002 Society of Photo-Optical Instrumentation Engineers.
Persistent Identifierhttp://hdl.handle.net/10722/42921
ISSN
2015 Impact Factor: 0.984
2015 SCImago Journal Rankings: 0.485
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorYang, XZen_HK
dc.contributor.authorPang, GKHen_HK
dc.contributor.authorYung, NHCen_HK
dc.date.accessioned2007-03-23T04:34:46Z-
dc.date.available2007-03-23T04:34:46Z-
dc.date.issued2002en_HK
dc.identifier.citationOptical Engineering, 2002, v. 41 n. 12, p. 3116-3126en_HK
dc.identifier.issn0091-3286en_HK
dc.identifier.urihttp://hdl.handle.net/10722/42921-
dc.description.abstractWe propose a new method for fabric defect detection by incorporating the design of an adaptive wavelet-based feature extractor with the design of an Euclidean distance-based detector. The proposed method characterizes the fabric image with multiscale wavelet features by using undecimated discrete wavelet transforms. Each nonoverlapping window of the fabric image is then detected as defect or nondefect with an Euclidean distance-based detector. Instead of using the standard wavelet bases, an adaptive wavelet basis is designed for the detection of fabric defects. Minimization of the detection error Is achieved by incorporating the design of the adaptive wavelet with the design of the detector parameters using a discriminative feature extraction (DFE) training method. The proposed method has been evaluated on 480 defect samples from five types of defects, and 480 nondefect samples, where a 97.5% detection rate and 0.63% false alarm rate were achieved. The evaluations were also carried out on unknown types of defects, where a 93.3% detection rate and 3.97% false alarm rate were achieved in the detection of 180 defect samples and 780 nondefect samples. © 2002 Society of Photo-Optical Instrumentation Engineers.en_HK
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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 2002 Society of Photo-Optical Instrumentation Engineers. This paper was published in Optical Engineering, 2002, v. 41 n. 12, p. 3116-3125 and is made available as an electronic reprint with permission of SPIE. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.en_HK
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.subjectAdaptive waveletsen_HK
dc.subjectDefect detectionen_HK
dc.subjectDiscriminative feature extractionen_HK
dc.subjectUndecimated discrete wavelet transformen_HK
dc.titleDiscriminative fabric defect detection using adaptive waveletsen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0091-3286&volume=41&issue=12&spage=3116&epage=3125&date=2002&atitle=Discriminative+fabric+defect+detection+using+adaptive+waveletsen_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.naturepublished_or_final_versionen_HK
dc.identifier.doi10.1117/1.1517290en_HK
dc.identifier.scopuseid_2-s2.0-0036980303en_HK
dc.identifier.hkuros81196-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-0036980303&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume41en_HK
dc.identifier.issue12en_HK
dc.identifier.spage3116en_HK
dc.identifier.epage3126en_HK
dc.identifier.isiWOS:000179954500018-
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridYang, XZ=7406505132en_HK
dc.identifier.scopusauthoridPang, GKH=7103393283en_HK
dc.identifier.scopusauthoridYung, NHC=7003473369en_HK

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