YAPAY GÖRME TABANLI KUMAŞ HATA TESPİT SİSTEMİ

Due to the cost and complexity of existing defect detection systems, a fabric defect detection device based on an artificial vision system has been developed in this study. Using knitted pile fabric, six types of defects were studied: loop drop, fly defect, grease spot, cross- striped defect, hole defect and pilling defect. Obtained fabric images were converted into histograms by a computer program developed within the scope of this study and defect types were characterized

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  • 1. Rallo, M., Sagrario Millan, M., Escofet, J., 2002, Wavelet-based Techniques for Textile Inspection, Grup d’Optica Aplicada I Processament d’Imatge de la Universitat Politecnica de Catalunya, Terrassa.
  • 2. G.K. Chan., 2016, Fabric Defect Detection by Fourier Analysis, IEEE Trans. Ind. Appl. 36(5), 1267-1276.
  • 3. H.Y.T. Ngan., G:K.H. Pang., N.H.C. Yung, 2011, Automated Fabric Defect Detection-a Review, Image Visiom Comput. 29, 442-458.
  • 4. Alam Eldin, A. T.,1988, Computer Vision for Automated Inspection of fabric Products, Ph. D. Thesis, University of Wuppertal, Germany.
  • 5. Chin, R.T., and Harlow, C.A:, 1982, Automated Visual Inspection: A survey, IEEE Trans. Pattern Anal. Machine Intell., 4(6), 557-573. 5. 6.Turgut, Y., 2013, Yapay Görmeye Dayalı Otomatik Hata Denetim Sistemi, Marmara Üniversitesi, Mekatronik Anabilim Dalı, FBE, Yüksek Lisans Tezi, İstanbul, Türkiye.
  • 6. Hormes, I., and Wulfhorst, B., 1995, Erkennung der Störpartikel mit Hilfe der digitalen Bildverabeitung Intern. Text.Bull. 41, Garn-u. Flachenherst 2-12.
  • 7. Watanabe, A., Konda, F., Kurosaki, S.N., 1995, Analysis of Blend Irregularity in Yarns Using Image Processing, Part:III: Evaluation of Blend Irregularity by Line Sense and its Aplication to Actual Blended Yarns, Textile Res. J., 65819, 392.
  • 8. Yang, W., Lu, S., Wang, S., Li, D., 2011, Fast Recognition of Foreign Fibers in Cotton Lint Using Machine Vision, Mathematical and Computer Modelling, 54, 877-882.
  • 9. Clark, A, D., Pauri, S, K., Hashim, A, A., 1986, Detection of Defects on Fabrics, IEE Colloquium on ‘’Image Processing for Automated Inspection’’ No:48, London, UK, April.
  • 10. Jasper, W, J., Potlapalli, H., 1995, Image Analysis of Mispicks in Woven Fabric, Textile research Journal, 65 (11), 683-692.
  • 11. Ribolzi, S, Merckle, J., Gresser, J., Exbrayat, P, E., 1993, Real time Defect Detection on Textiles using Opto-Electronic Processing, Textile Research Journal, 6382), 61-71.
  • 12. Shady, E., 1998, A computer Vision Systems for Automated Inspection of Fabrics’’ Master Thesis, Mansaura University, Egypt.
  • 13. Tsai, I, S., Hu, M, C., 2000, Automatic Inspection of Fabric Defects using an Artificial Neural Network
  • 14. Textile Handbook 2000, Hong Kong Productivity Council, The Hong Kong Cotton Spinners Association.
  • 15. Çelik, H.İ., Dülger, C.L., Topalbekiroğlu, M., 2012, Görüntü İşleme Teknikleri Kullanarak Kumaş Hatalarının Belirlenmesi, Elektronic Journal of Textile Technologies, 6, 22-39.
  • 16. Malek, A.S., 2012, Online Fabric Inspection by Image Processing Technology, Mechanical Engineering, University of Haute Alsace, France.
  • 17. Yapi, D.,Mejri, M., Allili, S. M., Baaziz, N., 2015, A Learning-Based Approach for Automatic Defect Detection in Textile Images, (IFAC), 48, 2423-2428.
  • 18. Kumar, A., 2008, Computer Vision-Based Fabric Defect Detection: A Survey, IEEE Transactions on Industrial Electronics, 55, 348-363.
  • 19. Hanbay, K., Talu, F.M., 2014, Kumaş Hatalarının Online/Ofline Tespit Sistemleri ve Yöntemleri, SAÜ, Fen Bilimleri Dergisi, 18, 46-69.
  • 20. Semnani, D., Vadood M., 2010 , Improvement Of Intelligent Methods For Evaluating The Apparent Quality Of Knitted Fabrics, Engineering Applications of Artificial Intelligence, 23, 217-221.
  • 21. Abou-iiana, M., Youssef, S., Pastore, C., and Gowayed, Y., 2003, Assesing Structural Changes in Knits during Processing, Textile Research Journal 73(6), 535-540.
  • 22. Saeidi, R. G., Latifi, M., Najar, S. S., Saeidi A, G., 2005, Computer Vision-Aided Fabric Inspecon System for On-Circular Knitting Machine, Textile Research Journal, 75 (6), 492-497.
  • 23. Shady, E., Gowayed, Y., Abouiiana, M., Youssef, S., Pastore, C., 2006, Detection and Classification of Defects in Knitted Fabric Structures, Textile Research Journal, 76 (4), 295-300.
  • 24. Mahajan, P. M., Kolhe, S. R., Pati, P.M., 2009, Areview of Automatic Fabric Defect Detection Techniques, Adv. Comput. Res. 1, 18-29.
  • 25. Campbell, J.G., and Murtagh, F., 1988, Automatic Visual Inspection of Woven Textiles using a two stage Defect Detector, Opt, Eng. 37, 2536-2542.
  • 26. Chan, C.H., and Pang, G., 2000, Fabric Defect Detection by Fourier Analysis, IEEE Trans. Ind.Appl. 36, 1267-1276.
  • 27. Tsai, D.M., and Heish, C. Y., 1999, Automated Surface Inspection for Directional Texturs, Image and Vision Comp., 18, 49-62.
  • 28. Lambert, G., and Bock, F., 1997, Wavelet Methods for Texture Defect Detection, Proc. IEEE Int. Conf. Image Processing, 3, 201-204.
  • 29. Mufti , M., 1995, Defect Detection and Identification using Fuzzy Wavelets, PhD Thesis, Georgia Institute of Technology.
  • 30. Alimohamadi H., Ahmadyfard A., Shojaee E., 2009, Defect Detection in Textiles Using Morphological Analysis of Optimal Gabor Wavelet Filter Response, in: Computer and Automation Engineering, ICCAE '09. International Conference, 26-30.
  • 31. Han, R., Zhang, L., 2009, Fabric Defect Detection Method Based on Gabor Filter Mask, Intelligent Systems, GCIS '09. WRI Global Congress, 3, 184-188.
  • 32. Bissi, L.,Baruffa, G., Placidi, P., Ricci, E., Scorzoni, A., Val,g,, P., 2013, Automated Defect Detection In Uniform And Structured Fabrics Using Gabor Filter Sand Pca, Visual Commun Image, 24, 838-845.
  • 33. Schmitt, R.,Fürjes, T., Abbas, B., Abel, P., Kimmelmann, W., Kosse, P., Buratti, A., 2015, Real-Time Machine Vision System For an Automated Quality Monitaring in Mass Production of Multiaxial Non-Crimp Fabrics, IFAC-Papers Online 48-3, 2393-2398.
  • 34. Carfagni M, Furferi R, Governi L, 2005, A Real-Time Machine Vision System For Monitoring The Textile Raisng Process, Computers In Industry, 56, 831842.
  • 35. Abouelela, A., Abbas, H.M., Eldeeb, H., Wahdan, A.A., Nassar, A.M., 2005, Automated Vision System For Localizing Structural Defects In Textile Fabrics, Pattern Recognition. Letters, 26, 1435-1443.