Integrated Computer Vision and Soft Computing System for Classifying the Pilling Resistance of Knitted Fabrics

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dc.contributor.authorEldessouki, Mohamed
dc.contributor.authorBukhari, Hanan A.
dc.contributor.authorHassan, Mounir
dc.contributor.authorQashqari, Khadijah
dc.date.accessioned2016-05-24
dc.date.available2016-05-24
dc.date.issued2014
dc.description.abstractFabric pilling is one of the important properties that affect fabric appearance. The testing of fabric pilling using the standard methods available, however, depends on subjective sample evaluation. Objective fabric pilling evaluation using image processing techniques comprises four main stages that include binarisation, segmentation, quantisation, and classification. Literature on the topic focuses only on one or more of these stages while there is a growing need for an integrated system that combines the most effective techniques of each stage and introduces them in a way that does not depend on the subjective evaluation of human operators. This work tries to tackle this problem and creates an integrated system for classifying the pilling resistance of knitted fabrics. The system introduced a new method for generating an image library based on photographs of the EMPA Standards to allow the training and testing of a soft-computing classifier. The method suggested was tested using knitted samples of different structures and colours and the results show their high robustness performance. The quantitative pilling classification produced from the system suggested shows high agreement with the subjective operatorsevaluation with a Spearman's correlation coefficient of +0.85.en
dc.description.sponsorshipDeanship of Scientific Research (DSR), King Abdulaziz University, Jeddah, Saudi Arabia [186/364/1433]; DSR
dc.formattext
dc.identifier.issn1230-3666
dc.identifier.scopus2-s2.0-84908324379
dc.identifier.urihttps://dspace.tul.cz/handle/15240/16381
dc.language.isoen
dc.publisherInst Chemical Fibres
dc.publisherTechnická Univerzita v Libercics
dc.publisherTechnical university of Liberec, Czech Republicen
dc.relation.ispartofFibres & Textiles In Eastern Europeen
dc.sourcej-scopus
dc.sourcej-wok
dc.subjectpilling of knitted fabricen
dc.subjectpill segmentationen
dc.subjectpill quantisationen
dc.subjectsoft-computing classifieren
dc.subjectartificial neural networksen
dc.titleIntegrated Computer Vision and Soft Computing System for Classifying the Pilling Resistance of Knitted Fabricsen
dc.typeArticle
local.accessopen
local.citation.epage112
local.citation.spage106
local.departmentDepartment of Materials Engineering
local.facultyFaculty of Textile Engineering
local.fulltextyes
local.identifier.stagRIV/46747885:24410/14:#0003699
local.identifier.wok344433900016
local.relation.issue6
local.relation.volume22
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