Image processing and analysis algorithms for yarn hairiness determination
نویسندگان
چکیده
منابع مشابه
Yarn Hairiness Determination Using Image Processing
Yarn hairiness is one of the key parameters influencing the quality of yarn.It is observed that yarn quality has been deduced based on yarn length and diameter only. But these parameters do not provide much information about yarn quality. Thus it is proposed to derive more yarn quality parameters like yarn hairiness, uniformity of yarn and its thickness. In textile industry, image processing is...
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Yarn hairiness has been an important indication of yarn quality that affects weaving production and fabric appearance. In addition to many dedicated instruments, various image analysis systems have been adopted to measure yarn hairiness for potential values of high accuracy and low cost. However, there is a common problem in acquiring yarn images; that is, hairy fibers protruding beyond the dep...
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This study is focused on the hairiness of worsted wool yarns and how it affects the pilling propensity of knitted wool fabrics. Conventional worsted ring spun yarns are compared with comparable Solospun yarns and yarns modified with a hairiness reducing air nozzle in the winding process (JetWind). Measurements of yarn hairiness (S3) on the Zweigle G565 hairiness meter shows a reduction in the S...
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This paper describes various illumination and image processing techniques for yarn characterization. Darkfield and back-lit illuminations are compared in terms of depth of field tolerance and image quality. Experiments show that back-lit illumination is superior in terms of depth of field tolerance and contrast. Three different back-lit illumination configurations are studied: one simply employ...
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ژورنال
عنوان ژورنال: Machine Vision and Applications
سال: 2012
ISSN: 0932-8092,1432-1769
DOI: 10.1007/s00138-012-0411-y