AN INTELLIGENT FABRIC DEFECT INSPECTION AND DETECTION SYSTEM USING IMAGE PROCESSING

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@article{1701150,
      author = {M.Archana, K.Kausalya, C.Monisha, Dr.S.Anila},
      title = {AN INTELLIGENT FABRIC DEFECT INSPECTION AND DETECTION SYSTEM USING IMAGE PROCESSING},
      journal = {Iconic Research And Engineering Journals},
      year = {2019},
      volume = {2},
      number = {10},
      pages = {220-224},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1701150.pdf},
      abstract = {In this modern era, people are much conscious on what they wear. Hence delivering a quality product without any defect is the weaver?s major concern. Local weavers daily wages are based on the quality product they produce but unfortunate defect due to transportation or some other may reflect their little penny. The existing fabric defect inspection system is made manually and are time consuming. The proposed methodology identifies the fabric defect using crossed area detection. The structure characteristics and texture features are obtained by using Gray Level Co-Occurrence Matrix (GLCM). Crossed area is detected by using a spatial domain integral projection approach. Proposed methodology also encompasses a fabric defect detection using crossed area detection.},
      keywords = {2-D Integral projection approach, Crossed-area detection, GLCM},
      month = {April},
  }