Unsupervised fabric defect detection with local spectra refinement (LSR)

Sahar Shakir*, Cihan Topal

*Bu çalışma için yazışmadan sorumlu yazar

Araştırma sonucu: Dergiye katkıMakalebilirkişi

3 Atıf (Scopus)

Özet

The inspection of fabric defects is of great importance, as undetected and uncorrected defects entail poor production quality and expensive compensation. Due to the variety of defect types and sizes, it is a very tedious task to perform inspection manually. There are numerous automated systems in the literature; however, most of them require a training scheme where clean and defective fabric samples are manually fed to the system. Because of the diversity of fabric patterns and defect classes, supervised systems reduce convenience and ease of use in real practice. In this study, we propose an unsupervised, robust fabric defect detection method using spectral domain analysis. The proposed algorithm has a very simple flow and can run without any prior training scheme. First, the algorithm splits the input textile image into smaller patches and computes a generic spectral representation of the fabric pattern. Then, the method detects defective regions by measuring dissimilarities between the spectral representation and all local patches of the input fabric. We also introduce a textile fabric dataset, i.e., Ten Fabrics Dataset, which consists of ten different types of fabrics with 27 of the most common textile defects. According to the extensive set of experiments on two different datasets, the proposed method outperforms the state-of-the-art by achieving up to 94% accuracy.

Orijinal dilİngilizce
Sayfa (başlangıç-bitiş)1091-1103
Sayfa sayısı13
DergiNeural Computing and Applications
Hacim36
Basın numarası3
DOI'lar
Yayın durumuYayınlandı - Oca 2024

Bibliyografik not

Publisher Copyright:
© 2023, The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature.

Parmak izi

Unsupervised fabric defect detection with local spectra refinement (LSR)' araştırma başlıklarına git. Birlikte benzersiz bir parmak izi oluştururlar.

Alıntı Yap