Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/20802
Title: An unsupervised method for dominant colour region segmentation in yarn-dyed fabrics
Authors: Luo, L
Shao, SJ
Shen, HL
Xin, JH 
Issue Date: 2013
Source: Coloration technology, 2013, v. 129, no. 6, p. 389-397 How to cite?
Journal: Coloration Technology 
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.
URI: http://hdl.handle.net/10397/20802
ISSN: 1472-3581
DOI: 10.1111/cote.12063
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