Integrated Computer Vision and Soft Computing System for Classifying the Pilling Resistance of Knitted Fabrics
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Date
2014
Journal Title
Journal ISSN
Volume Title
Publisher
Inst Chemical Fibres
Technická Univerzita v Liberci
Technical university of Liberec, Czech Republic
Technická Univerzita v Liberci
Technical university of Liberec, Czech Republic
Abstract
Fabric 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.
Description
Subject(s)
pilling of knitted fabric, pill segmentation, pill quantisation, soft-computing classifier, artificial neural networks
Citation
Item identifier
ISSN
1230-3666