Journals / Tekstil ve Mühendis / 2016 / Cilt: 23 - Sayı: 104

AUTOMATIC INSPECTION OF THE WARP-WEFT DENSITY USING IMAGE PROCESSING TECHNIQUES

KUMAŞ SIKLIKLARININ GÖRÜNTÜ İŞLEME TEKNİKLERİ İLE OTOMATİK OLARAK BELİRLENMESİ

Pages
247–262
DOI
—
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

On the other hand, it is obtained that Fourier analysis method, one of the frequency domain techniques, which depends on the counting of the harmonics of the yarns, provide more successful result than spatial techniques.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In this study, possibility of determining warp and weft yarn density of colored and figured plain and twill woven fabrics by Wiener filter, median filter, grey level co-occurrence matrix and gray line profile methods, which are spatial techniques, and by Fourier and wavelet transformation methods, which are frequency domain techniques, are investigated.
📊
Key Findings & Data:Considering the spatial techniques, the most successful technique that determines warp and weft densities of plain and twill fabrics is the median filter method.
💡
Conclusion & Impact:On the other hand, it is obtained that Fourier analysis method, one of the frequency domain techniques, which depends on the counting of the harmonics of the yarns, provide more successful result than spatial techniques.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

In this study, possibility of determining warp and weft yarn density of colored and figured plain and twill woven fabrics by Wiener filter, median filter, grey level co-occurrence matrix and gray line profile methods, which are spatial techniques, and by Fourier and wavelet transformation methods, which are frequency domain techniques, are investigated. Considering the spatial techniques, the most successful technique that determines warp and weft densities of plain and twill fabrics is the median filter method. The following successful techniques are Wiener filter and gray level co-occurrence matrix. On the other hand, it is obtained that Fourier analysis method, one of the frequency domain techniques, which depends on the counting of the harmonics of the yarns, provide more successful result than spatial techniques.

Özet

Bu çalışmada, uzamsal yöntemler olan Wiener filtre, medyan filtre, gri düzeyli eş-oluşum matrisi, gri sıra kesit teknikleri ile, frekans uzayı yöntemlerinden Fourier ve dalgacık dönüşümü teknikleri kullanılarak renkli ve desenli bezayağı ve dimi örgülü kumaşların çözgü ve atkı sıklıklarının belirlenme olanakları araştırılmıştır. Uzamsal yöntemler açısından, bezayağı ve dimi örgülü kumaşların çözgü ve atkı sıklıklarının belirlenmesinde en başarılı yöntem medyan filtre yöntemidir. Medyan filtre yöntemini, Wiener filtre ve gri düzeyli eş-oluşum matris yöntemleri izlemektedir. Diğer yandan, frekans uzayı yöntemlerinden Fourier analizi yöntemi, kumaş görüntülerinde bulunan örüntülerin frekans uzayındaki harmoniklerinin tespiti esasına dayanmakta ve uzamsal yöntemlere oranla daha yüksek başarım oranı elde etmektedir.

🔖

Cite This Article

ALDEMİR, E., ÖZDEMİR, H., KILINÇ, S. (2016). AUTOMATIC INSPECTION OF THE WARP-WEFT DENSITY USING IMAGE PROCESSING TECHNIQUES. Tekstil ve Mühendis, Cilt: 23 - Sayı: 104, 247–262. https://ajindex.com/articles/366071

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (10)

  1. Lin, J. J. (2002), Applying a Co-occurrence Matrix to Automatic Inspection of Weaving Density for Woven Fabrics, Textile Research Journal, 72, 486-490. Techniková, L. ve Tunák, M. (2013), Weaving Density Evaluation with the Aid of Image Analysis, Fibres & Textiles in Eastern Europe, 21(2), 74-79.
  2. Sari-sarraf, H. (1996), On-line Optical Measurement and Monitoring of Yarn Density in Woven Fabrics, Photonics China '96 Symposium on Automated Optical Inspection for Industry: Theory, Technology, and Application. Beijing, China, 444-452.
  3. Maros, T. ve Ales, L. (2004), Applying Spectral Analysis to Automatic Inspection of Weaving Density, 16th International Conference Structure and Structural Mechanics of Textiles. Liberec, Çek Cumhuriyeti. Pan R., Gao W., Li Z., Gou J., Zhang J., Zhu D. (2015), Measuring Thread Densities of Woven Fabric Using the Fourier Transform, FIBRES & TEXTILES in Eastern Europe, 23, 1(109), 35-40.
  4. Lachkar, A., Gadi T., Benslimane, R., D'Orazio, L., Martuscelli, E. (2003), Textile Woven-fabric Recognition by Using Fourier Image-analysis Techniques: Part I: A Fully Automatic Approach for Crossedpoints Detection, The Journal of The Textile Institute, 94(3-4), 194-201.
  5. Pan, R., Gao W., Liu, J., Wang, H., Qian, X. (2011), Automatic Inspection of Double-system-mélange Yarn-dyed Fabric Density with Color-gradient Image, Fibers and Polymers, 12(1), 127-131.
  6. Li, L.Q., Chen, X. ve Huang, X.B. (2005), Automatic Inspection of Weaving Density for Woven Fabrics Using Adaptive Wavelets, Journal of Donghua University, 31, 63- 65. Chan, C. Pang, G. (2000), Fabric Defect Detection by Fourier Analysis, IEEE Transactions on Industry Applications, 36(5), 1267-1276.
  7. Lachkar, A., Benslimane, R., D'Orazio, L., Martuscelli, E. (2005) Textile Woven Fabric Recognition Using Fourier Image Analysis Techniques: Part II - Texture Analysis for Crossed-States Detection, The Journal of The Textile Institute, 96(3), 179-183.
  8. Feng, Y.L. ve Li, R.Q. (2001), Automatic Measurement of Weave Count with Wavelet Transfer, Journal of Textile Research, 22, 30-31.
  9. Jing, J., Liu S. (2014) Automatic Density Detection of Woven Fabrics via Wavelet Transform, Journal of Information and Computational Science, 11(8), 2559-2568. Yili F., et al (2001), Automatic Measurement of Weave Count with Wavelet Transfer, Journal of Textile Research, 2001-02. 22(2), 94-95.
  10. Pan, R., Gao, W., Liu, J., Wang, H. ve Zhang, X. (2010), Automatic Detection of Structure Parameters of Yarn-dyed Fabric, Textile Resea