Real Time Defect Identification of White Fabric in Textile Industry using Computer Vision

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ID: 313298
2020
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Ranked #705 of 705 articles by views in Journal of Computing & Biomedical Informatics

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Abstract
This study focuses on the defect identification of white fabric in the textile industry based on quality control standards. The standard manual process for examining fabric defects are labor and cost expensive. In this study, a high-quality camera will be used to capture the image of the fabric moving from the conveyor belt that will be processed to identify defects such as horizontal or vertical stripes, yarn missing, bunching up, and stains. Comparative analysis of the machine learning technique will be performed to find the best method. The method will be evaluated on a dataset captured through the local textile industry. At the production level, if some defect is found the machine will stop working unless that defect is resolved.
Reference Key
imported_1777060354_69ebca02299cd Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Sajid Iqbal, Nadeem Ahmad, Ali Raza
Journal Journal of Computing & Biomedical Informatics
Year 2020
DOI
10.56979/101/2020/45
URL
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