Real-time detection of knitting fabric defects using shearlet transform

dc.contributor.author	Hanbay, K. and Talu, M.F. and Faruk Özgüven, Ö. and Öztürk, D.
dc.date.accessioned	2021-04-08T12:07:06Z
dc.date.available	2021-04-08T12:07:06Z
dc.date.issued	2019
dc.identifier	10.32710/tekstilvekonfeksiyon.448737
dc.identifier.issn	13003356
dc.identifier.uri	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85063950487&doi=10.32710%2ftekstilvekonfeksiyon.448737&partnerID=40&md5=7da975fae53bbc90c47dc80c7caf4a73
dc.identifier.uri	http://acikerisim.bingol.edu.tr/handle/20.500.12898/4215
dc.description.abstract	This paper proposes a vision-based fabric inspection system for the circular knitting machine. Firstly, a comprehensive fabric database called Fabric Defect Detection Database (FDDD) are constructed. To extract significant features of fabric images, shearlet transform is used. Means and variances are calculated from all subbands and combined into a high-dimensional feature vector. The proposed system is evaluated on a circular knitting machine in a textile factory. The real-time performance analysis is only carried out by inspecting single jersey knitted fabric. Our proposed system achieves the highest accuracy of 94.0% in the detection of single jersey knitting fabric defects. © 2019 Ege Universitesi. All rights reserved.
dc.language.iso	English
dc.source	Tekstil ve Konfeksiyon
dc.title	Real-time detection of knitting fabric defects using shearlet transform

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