Yarn Quality detection for Textile Industries using Image Processing

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Kazi Kutubuddin Sayyad Liyakat, Nilima S. Warhade, Rahul S. Pol, Hemlata M. Jadhav, Altaf O. Mulani


In textile industry, estimating Yarn’s Quality becomes difficult task. In common cases; the task is completed manually.  A  Microscopic investigation for yarn quality estimation    necessitates significant amount of physical efforts as well as timing, as well as compromise on quality judgment uniformity. It’s nevertheless, a classic challenge during Yarn-based studies, whereas accurate yarn’s quality manufacture is determined using mathematical Yarn attributes such as length, and Diameter among others. In Previous researches, it is observed that Yarn Quality is calculated only depends on Yarn’s Length and Diameter. However,  these  criteria  alone  do  not  allow  for  many  mixing  permutations  and  combinations  in  order to make various quality variant Yarns. We  suggested  in  this  paper  to  develop  more Yarn characteristics from yarn (cotton)  with  much  more  precision,  like  Yarn’s  regularity  throughout  the  yarn  thickness,  hairiness,  small  colour  change, or contaminants.

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