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Digital Image Processing Technology for Measuring Yarn Hairiness in the Field of Textile


Affiliations
1 Department of Computer Science, CMS College of Science & Commerce, Coimbatore, Tamil Nadu, India
     

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This paper aims to review the recent trends in measuring yarn hairiness and the digital description, impartial assessment of yarn appearance are processed under the new approaches named digital image processing technology. The traditional detection methods and this new developed method were associated with each other which are made and analysed. When compared with the traditional methods, image-based methods have the advantages of being objective, fast and precise. Consequently, it perceived the yarn under a microscope and procurement a trace of hairs proved that the new trends are created in yarn appearance evaluation. The various indirect techniques for measuring yarn hairiness are developed, regarding the growth in its high commercial use of yarn increases. An endeavour was made in this work too reduce the risk and improve to automate the task using image processing technology. The first step is to develop the relevant algorithm proficient of analysing yarn hairiness image .The second step to minimize the need of requirement in this process of image actuation. In this work the best yarn hairiness indicator is recommended than traditional methods definition.

Keywords

Hairiness Measurement, Hairiness Modeling, Yarn Spinning, Image Processing, Segmentation, Yarn Hairiness.
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  • Digital Image Processing Technology for Measuring Yarn Hairiness in the Field of Textile

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Authors

R. Sudha
Department of Computer Science, CMS College of Science & Commerce, Coimbatore, Tamil Nadu, India
V. Chitraa
Department of Computer Science, CMS College of Science & Commerce, Coimbatore, Tamil Nadu, India

Abstract


This paper aims to review the recent trends in measuring yarn hairiness and the digital description, impartial assessment of yarn appearance are processed under the new approaches named digital image processing technology. The traditional detection methods and this new developed method were associated with each other which are made and analysed. When compared with the traditional methods, image-based methods have the advantages of being objective, fast and precise. Consequently, it perceived the yarn under a microscope and procurement a trace of hairs proved that the new trends are created in yarn appearance evaluation. The various indirect techniques for measuring yarn hairiness are developed, regarding the growth in its high commercial use of yarn increases. An endeavour was made in this work too reduce the risk and improve to automate the task using image processing technology. The first step is to develop the relevant algorithm proficient of analysing yarn hairiness image .The second step to minimize the need of requirement in this process of image actuation. In this work the best yarn hairiness indicator is recommended than traditional methods definition.

Keywords


Hairiness Measurement, Hairiness Modeling, Yarn Spinning, Image Processing, Segmentation, Yarn Hairiness.

References