Real time fabric defect detection by using fourier transform
Küçük Resim Yok
Tarih
2017
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Gazi Univ, Fac Engineering Architecture
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
In fabric productions, real time defect detection systems are needed to detect the surface defects. There is currently no real time defect detection system in knitting fabric production. In this paper, a real time fabric defect detection system is developed and is tested on circular knitting machine. Textural features of fabric image are extracted based on Fourier transform. These textural features are seven and are calculated from the horizontal and vertical directions of Fourier frequency spectrum of the fabric image. The performance of the proposed method is firstly evaluated off-line through experiments based on comprehensive fabric database. The proposed method obtains superior performance, which also proves its utility in real-time inspection. Secondly, a real time machine-vision system has been designed for an efficient detection of the fabric defects under industrial conditions. Real time defect detection system is tested automatically by analyzing fabric images captured by a line scan camera. Experimental results show that the proposed detection model can successfully detect common circular knitting fabric defects.
Açıklama
Anahtar Kelimeler
Fabric defect detection, real time inspection, texture classification, Fourier transform
Kaynak
Journal of The Faculty of Engineering and Architecture of Gazi University
WoS Q Değeri
Q3
Scopus Q Değeri
Q2
Cilt
32
Sayı
1
