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dc.contributor.authorHanbay, K. and Talu, M.F. and Özgüven, Ö.F.
dc.date.accessioned2021-04-08T12:08:26Z
dc.date.available2021-04-08T12:08:26Z
dc.date.issued2016
dc.identifier10.1016/j.ijleo.2016.09.110
dc.identifier.issn00304026
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84990856247&doi=10.1016%2fj.ijleo.2016.09.110&partnerID=40&md5=40b1f3d6c368d304dba200e20f269717
dc.identifier.urihttp://acikerisim.bingol.edu.tr/handle/20.500.12898/4597
dc.description.abstractThis paper presents a comprehensive literature review of fabric defect detection methods First, it briefly explains basic image acquisition system components such as camera and lens. Defect detection methods are categorized into seven classes as structural, statistical, spectral, model-based, learning, hybrid and comparison studies. These methods are evaluated according to such criteria as the accuracy, the computational cost, reliability, rotating/scaling invariant, online/offline ability to operate and noise sensitivity. Strengths and weaknesses of each approach are comparatively highlighted. In addition, the availability of utilizing methods for weaving and knitting in machines is investigated. The available review studies do not provide sufficient information about fabric defect detection systems for readers engaged in research in the area of textile and computer vision. A set of examination for efficient establishment of image acquisition system are added. In particular, lens and light source selection are mathematically expressed. © 2016
dc.language.isoEnglish
dc.sourceOptik
dc.titleFabric defect detection systems and methods—A systematic literature review


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