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Fabric patterns recognition based on weft phase difference

  • Zhejiang University
  • Lianshui Tiangong Fabric Manufacture Co., Ltd.

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Scopus citations

Abstract

For the purpose of identifying yarn density and fabric weave patterns, a novel method for fabric patterns recognition is proposed. The methods of gray-level integral projection and discrete Fourier transform are used to estimate yarn density in this paper. To avoid errors caused by noise, yarn deformation and illumination,yarn statistics are used. The concept of the weft phase difference is proposed which is the key point to derive the fabric patterns. Finally, a pattern with minimum error is identified. Two experiments are used to evaluate the proposed method. It is shown that our method is effective and robust. For some other methods, it is ineffective for large-scale repeat unit satin fabrics. However, our approach is still effective.

Original languageEnglish
Title of host publicationProceedings of the 38th Chinese Control Conference, CCC 2019
EditorsMinyue Fu, Jian Sun
PublisherIEEE Computer Society
Pages7810-7815
Number of pages6
ISBN (Electronic)9789881563972
DOIs
StatePublished - Jul 2019
Externally publishedYes
Event38th Chinese Control Conference, CCC 2019 - Guangzhou, China
Duration: 27 Jul 201930 Jul 2019

Publication series

NameChinese Control Conference, CCC
Volume2019-July
ISSN (Print)1934-1768
ISSN (Electronic)2161-2927

Conference

Conference38th Chinese Control Conference, CCC 2019
Country/TerritoryChina
CityGuangzhou
Period27/07/1930/07/19

Keywords

  • Discrete Fourier transform (DFT)
  • Fabric analysis
  • Fabric patterns
  • Gray-level integral projection
  • Yarn density

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