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http://hdl.handle.net/11452/30039
Title: | Image processing based drape measurement of fabrics using circular Hough transformation |
Authors: | Bursa Uludağ Üniversitesi/Mühendislik Fakültesi/Tekstil Mühendisliği Bölümü. 0000-0001-5708-7993 Süvari, Fatih N-1770-2019 55512827100 |
Keywords: | Hough transform Drape Fabric testing Image processing Behavior Materials science Appearance Cutting Fabric Measurement Processing Testing Weaving Weighing Feature extraction Hough transforms Instrument testing Knit fabrics Textile industry Weaving Aesthetic property Circular Hough transforms Conventional systems Correlation coefficient Hough transformation Image processing - methods Image processing algorithm Objective measurement Image processing |
Issue Date: | 9-Jun-2020 |
Publisher: | Taylor & Francis |
Citation: | Süvari, F. (2021). "Image processing based drape measurement of fabrics using circular Hough transformation". Journal of the Textile Institute, 112(5), 846-854. |
Abstract: | The drape behaviour of fabric is regarded as an aesthetic property, especially in the apparel and home textile industries. It has an influence on how well the appearance of a fabric in the end use. Fabric drape testing instrument developed by Cusick has been commonly used for the objective measurement of fabric drape behaviour. The device and the classic cut-and-weigh procedure is still the standard method of measuring drape. This method needs consumables and skilled operator for drawing, cutting, and weighing operations. To eliminate the disadvantages of this conventional system, image processing algorithm based on the Circular Hough Transform is developed to calculate the drape coefficient of fabrics in this study. Various woven and knitted fabrics were tested by both the conventional and the developed image processing methods. Drape results obtained from both systems represented a very strong relationship with a correlation coefficient of 0.99. As a result, fast, accurate and robust objective fabric drape test method has been developed. |
URI: | https://doi.org/10.1080/00405000.2020.1782553 https://www.tandfonline.com/doi/full/10.1080/00405000.2020.1782553 http://hdl.handle.net/11452/30039 |
ISSN: | 0040-5000 1754-2340 |
Appears in Collections: | Web of Science |
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