Rapid Classification of Textile Fabrics Arranged in Piles

Dirk Siegmund, Olga Kaehm, David Handtke

2016

Abstract

Research on the quality assurance of textiles has been a subject of much interest, particularly in relation to defect detection and the classification of woven fibers. Known systems require the fabric to be flat and spread-out on 2D surfaces in order for it to be classified. Unlike other systems, this system is able to classify textiles when they are presented in piles and in assembly-line like environments. Technical approaches have been selected under the aspects of speed and accuracy using 2D camera image data. A patch-based solution was chosen using an entropy-based pre-selection of small image patches. Interest points as well as texture descriptors combined with principle component analysis were part of this evaluation. The results showed that a classification of image patches resulted in less computational cost but reduced accuracy by 3.67%.

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Paper Citation


in Harvard Style

Siegmund D., Kaehm O. and Handtke D. (2016). Rapid Classification of Textile Fabrics Arranged in Piles . In Proceedings of the 13th International Joint Conference on e-Business and Telecommunications - Volume 5: SIGMAP, (ICETE 2016) ISBN 978-989-758-196-0, pages 99-105. DOI: 10.5220/0005969300990105


in Bibtex Style

@conference{sigmap16,
author={Dirk Siegmund and Olga Kaehm and David Handtke},
title={Rapid Classification of Textile Fabrics Arranged in Piles},
booktitle={Proceedings of the 13th International Joint Conference on e-Business and Telecommunications - Volume 5: SIGMAP, (ICETE 2016)},
year={2016},
pages={99-105},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005969300990105},
isbn={978-989-758-196-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 13th International Joint Conference on e-Business and Telecommunications - Volume 5: SIGMAP, (ICETE 2016)
TI - Rapid Classification of Textile Fabrics Arranged in Piles
SN - 978-989-758-196-0
AU - Siegmund D.
AU - Kaehm O.
AU - Handtke D.
PY - 2016
SP - 99
EP - 105
DO - 10.5220/0005969300990105