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Evaluation of fabric pilling as an end-use quality and a performance measure for the fabrics

Identifikátory výsledku

  • Kód výsledku v IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F46747885%3A24410%2F17%3A00004281" target="_blank" >RIV/46747885:24410/17:00004281 - isvavai.cz</a>

  • Výsledek na webu

    <a href="http://www.sciencedirect.com/science/article/pii/B9780081012178000075" target="_blank" >http://www.sciencedirect.com/science/article/pii/B9780081012178000075</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1016/B978-0-08-101217-8.00007-5" target="_blank" >10.1016/B978-0-08-101217-8.00007-5</a>

Alternativní jazyky

  • Jazyk výsledku

    angličtina

  • Název v původním jazyce

    Evaluation of fabric pilling as an end-use quality and a performance measure for the fabrics

  • Popis výsledku v původním jazyce

    © 2018 Elsevier Ltd. All rights reserved. Fabric pilling is considered a performance and esthetic property of the fabrics and determines its quality. Nevertheless, the subjective evaluation of the fabric pilling results in misleading values that depend on the measurement standard even for the same sample. This extensively reviews the methods used in the literature to quantify the fabric pilling, then utilizes some of the nonused textural features extracted from the fabric's images to obtain better representative and quantitative values of the fabric's surface. The algorithms for creating the features datasets for training and testing the soft-computing classifiers were described where random noise was added to the limited number of fabric's pilling standard images. The theoretical background for using fuzzy logic and its working mechanism when implemented in the adaptive neuro-fuzzy system (ANFIS) was explained in this chapter, then the practical applications for an objective pilling classification (PC) of woven fabric samples were performed using ANFIS and for knitted samples were performed using the artificial neural network. The soft-computing classifiers showed an ability to classify the noised standard images as well as actual fabric samples with a classification rate that shows high correlation coefficients when compared with the classification grades of the human operators. Results showed high efficiency of the system that is independent on the different fabric structure or color, which suggests its availability to replace the currently applied subjective pilling evaluation.

  • Název v anglickém jazyce

    Evaluation of fabric pilling as an end-use quality and a performance measure for the fabrics

  • Popis výsledku anglicky

    © 2018 Elsevier Ltd. All rights reserved. Fabric pilling is considered a performance and esthetic property of the fabrics and determines its quality. Nevertheless, the subjective evaluation of the fabric pilling results in misleading values that depend on the measurement standard even for the same sample. This extensively reviews the methods used in the literature to quantify the fabric pilling, then utilizes some of the nonused textural features extracted from the fabric's images to obtain better representative and quantitative values of the fabric's surface. The algorithms for creating the features datasets for training and testing the soft-computing classifiers were described where random noise was added to the limited number of fabric's pilling standard images. The theoretical background for using fuzzy logic and its working mechanism when implemented in the adaptive neuro-fuzzy system (ANFIS) was explained in this chapter, then the practical applications for an objective pilling classification (PC) of woven fabric samples were performed using ANFIS and for knitted samples were performed using the artificial neural network. The soft-computing classifiers showed an ability to classify the noised standard images as well as actual fabric samples with a classification rate that shows high correlation coefficients when compared with the classification grades of the human operators. Results showed high efficiency of the system that is independent on the different fabric structure or color, which suggests its availability to replace the currently applied subjective pilling evaluation.

Klasifikace

  • Druh

    C - Kapitola v odborné knize

  • CEP obor

  • OECD FORD obor

    20503 - Textiles; including synthetic dyes, colours, fibres (nanoscale materials to be 2.10; biomaterials to be 2.9)

Návaznosti výsledku

  • Projekt

    <a href="/cs/project/LO1201" target="_blank" >LO1201: ROZVOJ ÚSTAVU PRO NANOMATERIÁLY, POKROČILÉ TECHNOLOGIE A INOVACE TECHNICKÉ UNIVERZITY V LIBERCI</a><br>

  • Návaznosti

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Ostatní

  • Rok uplatnění

    2017

  • Kód důvěrnosti údajů

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Údaje specifické pro druh výsledku

  • Název knihy nebo sborníku

    Applications of Computer Vision in Fashion and Textiles

  • ISBN

    978-0-08-101217-8

  • Počet stran výsledku

    41

  • Strana od-do

    147-187

  • Počet stran knihy

    302

  • Název nakladatele

    Woodhead Publishing

  • Místo vydání

  • Kód UT WoS kapitoly