Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/14758
Title: A new method for classification of woven structure for yarn-dyed fabric
Authors: Zheng, D
Han, Y
Hu, JL 
Keywords: Crossing point
Fabric image processing
Fiber orientation
Radon transform
Woven pattern recognition
Yarn float
Issue Date: 2014
Publisher: SAGE Publications
Source: Textile research journal, 2014, v. 84, no. 1, p. 78-95 How to cite?
Journal: Textile research journal 
Abstract: The fabric weave pattern recognition process is a structure identification process that detects the yarn location as well as the yarn crossing structure in a woven fabric. A new local orientation feature is proposed for fabric structure detection by using high-resolution images. The detection process consists of two main steps. Firstly, the yarn location is detected through a series of image enhancement techniques and an edge-based projection method. Secondly, the yarn float is recognized with a local orientation detection approach based on Radon transform. Three kinds of yarn-dyed cotton fabrics are investigated in this study, including the single yarn, the double yarn, and the twisted yarn fabric. Experimental results and discussions demonstrate that the research method is effective in detecting fabric structure and yarn float even with long hairiness.
URI: http://hdl.handle.net/10397/14758
ISSN: 0040-5175
EISSN: 1746-7748
DOI: 10.1177/0040517513483858
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