Fabric defect detection systems and methods-A systematic literature review

Hanbay K., TALU M. F., Ozguven O. F.

OPTIK, cilt.127, sa.24, ss.11960-11973, 2016 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Derleme
  • Cilt numarası: 127 Sayı: 24
  • Basım Tarihi: 2016
  • Doi Numarası: 10.1016/j.ijleo.2016.09.110
  • Dergi Adı: OPTIK
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.11960-11973
  • Anahtar Kelimeler: Fabric defect detection, Texture analysis, Image processing, Textile inspection, Image acquisition systems, NEURAL-NETWORK, WAVELET TRANSFORM, TEXTURAL FEATURES, GABOR FILTER, CLASSIFICATION, SEGMENTATION, QUALITY, INSPECTION, FOURIER, MODEL
  • İnönü Üniversitesi Adresli: Evet

Özet

This paper presents a comprehensive literature review of fabric defect detection methods First, it briefly explains basic image acquisition system components such as camera and lens. Defect detection methods are categorized into seven classes as structural, statistical, spectral, model-based, learning, hybrid and comparison studies. These methods are evaluated according to such criteria as the accuracy, the computational cost, reliability, rotating/scaling invariant, online/offline ability to operate and noise sensitivity. Strengths and weaknesses of each approach are comparatively highlighted. In addition, the availability of utilizing methods for weaving and knitting in machines is investigated. The available review studies do not provide sufficient information about fabric defect detection systems for readers engaged in research in the area of textile and computer vision. A set of examination for efficient establishment of image acquisition system are added. In particular, lens and light source selection are mathematically expressed. (C) 2016 Elsevier GmbH. All rights reserved.