Textural fabric defect detection using statistical texture transformations and gradient search

Selver M. A., Avsar V., Özdemir H.

JOURNAL OF THE TEXTILE INSTITUTE, cilt.105, sa.9, ss.998-1007, 2014 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 105 Sayı: 9
  • Basım Tarihi: 2014
  • Doi Numarası: 10.1080/00405000.2013.876154
  • Dergi Adı: JOURNAL OF THE TEXTILE INSTITUTE
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.998-1007
  • Anahtar Kelimeler: fabric defect detection, industrial defect detection, automated visual inspection, textile inspection, statistical texture deformations, sum and difference histograms, COMPUTER-VISION, CLASSIFICATION, INSPECTION, FEATURES
  • Dokuz Eylül Üniversitesi Adresli: Evet

Özet

The inspection of the fabric defects is an important problem, which highly affects both the quality and the cost in the textile industry. Because of consistency and accuracy problems, the inspection of the fabric defect by human experts is neither feasible nor efficient. This requires development and use of automated inspection techniques. Thus, in this study, a texture analysis method, which uses sum and difference histograms (SDH) conjointly with co-occurrence matrices, is proposed to introduce an objective criterion for defect detection. To accomplish the detection task with high accuracy, several features were extracted from SDH and then, a defect search technique, which was developed in the context of this study, was applied. Moreover, several experiments and parameter analysis were performed to carry out detection at feasible computation time and memory storage. The developed method was applied to 28 kinds of raw woven fabric defects and 27 of them (i.e. 93.1%) were successfully recognized by the proposed detection system. The quantitative results and qualitative discussions show the effectiveness of the developed strategy.