Review of Printed Fabric Pattern Segmentation Analysis and Application

• Autorzy: Kumah Charles , Raji Rafiu King , Pan Ruru

Identyfikatory

DOI

10.2478/aut-2019-0049

• Języki publikacji: EN

Abstrakty

EN

Image processing of digital images is one of the essential categories of image transformation in the theory and practice of digital pattern analysis and computer vision. Automated pattern recognition systems are much needed in the textile industry more importantly when the quality control of products is a significant problem. The printed fabric pattern segmentation procedure is carried out since human interaction proves to be unsatisfactory and costly. Hence, to reduce the cost and wastage of time, automatic segmentation and pattern recognition are required. Several robust and efficient segmentation algorithms are established for pattern recognition. In this paper, different automated methods are presented to segregate printed patterns from textiles fabric. This has become necessary because quality product devoid of any disturbances is the ultimate aim of the textile printing industry.

Słowa kluczowe

EN

image segmentation; printed patterns; automatic inspection; pattern recognition

PL

segmentacja obrazu; drukowane wzory; rozpoznawanie wzorców

• Wydawca: Lodz University of Technology, Faculty of Material Technologies and Textile Design
• Czasopismo: Autex Research Journal
• Rocznik: 2020
• Tom: Vol. 20, no. 4
• Strony: 530--538
• Opis fizyczny: Bibliogr. 79 poz.

Twórcy

autor

Kumah Charles

• Key Laboratory of Eco-textiles, Ministry of Education, School of Textile & Clothing, Jiangnan University, Wuxi, 214122, China

autor

Raji Rafiu King

• Engineering Research Centre of Knitting Technology, Ministry of Education, Jiangnan University, PRC

autor

Pan Ruru

• Key Laboratory of Eco-textiles, Ministry of Education, School of Textile & Clothing, Jiangnan University, Wuxi, 214122, China

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).