Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/434758
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dc.coverage.spatialAutomatic fabric defect detection and classification by using image processing technology
dc.date.accessioned2023-01-02T06:08:12Z-
dc.date.available2023-01-02T06:08:12Z-
dc.identifier.urihttp://hdl.handle.net/10603/434758-
dc.description.abstractMachine vision encompasses all industrial and non-industrial applications in which a combination of hardware and software provide operational guidance to devices in the execution of their functions based on the capture and processing of images. One of the important applications of machine vision is fabric inspection. newlineFabric inspection is a necessary and essential step of quality control in the textile manufacturing industry. All textile industries aim to produce competitive fabrics. The competition depends mainly on productivity and quality of the fabrics produced by each industry. In the textile sector, there have been an enlarge amount of losses due to faulty fabrics. So automatic fabric inspection is developed to solve these issues. newlineAutomatic fabric inspection offer a no of potential advantages, including improved safety, reduced labor costs, elimination of human error and subjective judgment. An automatic fabric defect recognition system consists of preprocessing, detection and classification. newline
dc.format.extentxix,140p.
dc.languageEnglish
dc.relationp.130-139
dc.rightsuniversity
dc.titleAutomatic fabric defect detection and classification by using image processing technology
dc.title.alternative
dc.creator.researcherFathu Nisha M
dc.subject.keywordEngineering and Technology
dc.subject.keywordComputer Science
dc.subject.keywordComputer Science Information Systems
dc.subject.keywordFabric images
dc.subject.keywordScanning process
dc.subject.keywordtransformation
dc.description.note
dc.contributor.guideVasuki P
dc.publisher.placeChennai
dc.publisher.universityAnna University
dc.publisher.institutionFaculty of Information and Communication Engineering
dc.date.registered
dc.date.completed2021
dc.date.awarded2021
dc.format.dimensions21 cm
dc.format.accompanyingmaterialNone
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Faculty of Information and Communication Engineering

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01_title.pdfAttached File27.59 kBAdobe PDFView/Open
02_prelim pages.pdf2.89 MBAdobe PDFView/Open
03_content.pdf22.87 kBAdobe PDFView/Open
04_abstract.pdf13.64 kBAdobe PDFView/Open
05_chapter 1.pdf669.62 kBAdobe PDFView/Open
06_chapter 2.pdf1.01 MBAdobe PDFView/Open
07_chapter 3.pdf797.36 kBAdobe PDFView/Open
08_chapter 4.pdf1.37 MBAdobe PDFView/Open
09_chapter 5.pdf938.94 kBAdobe PDFView/Open
10_annexures.pdf112.53 kBAdobe PDFView/Open
80_recommendation.pdf50.33 kBAdobe PDFView/Open


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