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dc.contributor.authorSelvanayaki M-
dc.date.accessioned2020-09-15T05:49:19Z-
dc.date.available2020-09-15T05:49:19Z-
dc.date.issued2017-12-
dc.identifier.issn0974-9683-
dc.identifier.urihttp://www.ciitresearch.org/dl/index.php/dmke/article/view/DMKE112017003.-
dc.identifier.urihttp://localhost:8080/xmlui/handle/123456789/1487-
dc.description.abstractImage processing is applied in several real-time industrial applications. Image vision and automated visual inspection is one such primary application in textile industry. This survey research articles presents a widespread literature review in the fabric defect detection problem domain. In this article, a brief introduction to fabric defect prediction is presented. Then fabric defect detection components are discussed. After that, several research works are reviewed. The primary performance metric is given and the openly available dataset information are then portrayed followed with concluding remarks. Defect detection methods are discussed that comes under several categories namely structural, statistical, spectral, model-based, learning, hybrid and comparison studies.en_US
dc.language.isoenen_US
dc.publisherInternational Journal of Data Mining and Knowledge Engineeringen_US
dc.subjectImage Processingen_US
dc.subjectFabric Defect Detectionen_US
dc.subjectFabric Defect Detection Dataseten_US
dc.subjectAccuracyen_US
dc.subjectFibreen_US
dc.titleFABRIC DEFECT DETECTION – A SURVEYen_US
dc.typeArticleen_US
Appears in Collections:International Journals

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