An unsupervised method for dominant colour region segmentation in yarn-dyed fabrics

Lin Luo, Si Jie Shao, Hui Liang Shen, John Haozhong Xin

Research output: Journal article publicationJournal articleAcademic researchpeer-review

18 Citations (Scopus)

Abstract

This paper presents a novel unsupervised approach to detect dominant colour regions standing out conspicuously in yarn-dyed fabric images. For a dominant colour region of a yarn-dyed fabric, measured by an imaging system, its individual yarn has an irregular three-dimensional shape resulting in significant colour difference among pixels of the yarn. This difference leads to difficulty in segmenting yarns into dominant colour regions. A probabilistic model is proposed in this study to associate the colour of a dominant colour region with the colours of its yarns. Based on this model, the colour histograms of a dominant colour region are first estimated from those of yarns in a yarn-dyed fabric image. Then, a hierarchical segmentation structure is devised to detect dominant colour regions in the image. Experimental results show that the proposed approach achieves satisfactory performance for dominant colour region segmentation in yarn-dyed fabric images, with high computational efficiency.
Original languageEnglish
Pages (from-to)389-397
Number of pages9
JournalColoration Technology
Volume129
Issue number6
DOIs
Publication statusPublished - 1 Dec 2013

ASJC Scopus subject areas

  • Chemistry (miscellaneous)
  • Chemical Engineering(all)
  • Materials Science (miscellaneous)

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