Real-Time Detection of Knitting Fabric Defects Using Shearlet Transform
Küçük Resim Yok
Tarih
2019
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Ege Univ
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
This paper proposes a vision-based fabric inspection system for the circular knitting machine. Firstly, a comprehensive fabric database called Fabric Defect Detection Database (FDDD) are constructed. To extract significant features of fabric images, shearlet transform is used. Means and variances are calculated from all subbands and combined into a high-dimensional feature vector. The proposed system is evaluated on a circular knitting machine in a textile factory. The real-time performance analysis is only carried out by inspecting single jersey knitted fabric. Our proposed system achieves the highest accuracy of 94.0% in the detection of single jersey knitting fabric defects.
Açıklama
Anahtar Kelimeler
Fabric defect detection, real-time inspection, texture classification
Kaynak
Tekstil Ve Konfeksiyon
WoS Q Değeri
Q4
Scopus Q Değeri
Q3
Cilt
29
Sayı
1
