A computer vision-based system for automatic detection of misarranged color warp yarns in yarn-dyed fabric. Part III: yarn layout proofing

Jingan Wang, Jie Zhang, Lei Wang, Ruru Pan, Jian Zhou, Weidong Gao

Research output: Journal article publicationJournal articleAcademic researchpeer-review

1 Citation (Scopus)

Abstract

This series of studies aims to develop a computer vision-based system for automatic detection of misarranged color warp yarns. This paper proposes a yarn layout proofing strategy, integrating with the warp yarn segmentation and fabric image stitching methods proposed in Part I and warp region segmentation method proposed in Part II, to achieve system automation. In the previous papers, the widths of warp regions and the layout of color yarns in the tested fabric stripe are extracted from the captured fabric frame images. In this paper, through analyzing different forms of misarranged color warps, a standard yarn layout-based proofing strategy is developed to detect the misarranged color warp yarns. Experiment results demonstrate that the proposed method is proposing for the layout proofing of color warp yarns in multicolor yarn-dyed fabrics of color stripes and color checks with satisfactory accuracy and good robustness.
Original languageEnglish
Number of pages9
JournalJournal of the Textile Institute
DOIs
Publication statusPublished - 11 Mar 2020

Keywords

  • Misarranged color yarns
  • layout of color yarns
  • yarn layout proofing
  • yarn-dyed fabric

ASJC Scopus subject areas

  • Materials Science (miscellaneous)
  • Agricultural and Biological Sciences(all)
  • Polymers and Plastics
  • Industrial and Manufacturing Engineering

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