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AN IMAGE PROCESSING RESEARCH CONSISTENT WITH STANDARD PHOTOGRAPHS TO DETERMINE PILLING GRADE OF WOVEN FABRICS

Year 2019, Volume: 29 Issue: 3, 268 - 276, 30.09.2019
https://doi.org/10.32710/tekstilvekonfeksiyon.621184

Abstract

In this study, MATLAB 2018a software was used
to evaluate pilling grade of woven fabrics objectively. Experimental works were
carried out on the EMPA W3 standard photographs and accordingly two woven
fabrics. Equations were built based on the measurements of pill characteristics
and textural parameters of these photographs with the help of curve fitting
method after image processing steps. Intervals were generated for each fabric
by using slope of these equations and quantitative parameters obtained from the
original fabric. Furthermore, fabrics that were provided pilling formation at
different test turns were evaluated subjectively by expert operators. Objective
results corresponding to each parameter were analyzed comparatively with these
subjective results.
The developed method was successful by using mean of matrix elements
from textural parameters and total area from pill characteristics. 

References

  • 1. Ukponmwan JO, Mukhopadhyay A, Chatterjee KN. 1998. Pilling. Textile progress 28(3), 1-57.
  • 2. Özdil N. 2003. Kumaşlarda fiziksel kalite kontrol yöntemleri, E.Ü. Tekstil ve Konfeksiyon Araştırma Uygulama Merkezi Yayınları Yayın No: 21, ISBN No: 975-483-579-9, Bornova-İzmir, 120s.
  • 3. Özçelik G. 2009. Kumaş boncuklanma özelliğinin objektif olarak değerlendirilmesi ve tahminlenmesi üzerine bir araştırma, E.Ü. Fen Bilimleri Enstitüsü Doktora Tezi, Bornova-İzmir, 291s.
  • 4. Kayseri GÖ, Kirtay E. 2015. Part 1. Predicting the pilling tendency of the cotton interlock knitted fabrics by regression analysis. Journal of Engineered Fibers and Fabrics 10(3), 155892501501000305.
  • 5. Kayseri GÖ, Kirtay E. 2015. Part II. Predicting the pilling tendency of the cotton interlock knitted fabrics by artificial neural network. Journal of Engineered Fibers and Fabrics 10(4), 155892501501000417.
  • 6. Telli A. 2015, April. The reliability of subjective assessment in the determination of pilling resistance of knitted fabrics, 4th International Mediterranean Science and Engineering Congress (IMSEC 2019), 420-422.
  • 7. Furferi R, Governi L, Volpe Y. 2015. Machine vision-based pilling assessment: a review. Journal of Engineered Fibers and Fabrics 10(3), 155892501501000320.
  • 8. Wong C. (Ed.). 2017. Applications of Computer Vision in Fashion and Textiles. Woodhead Publishing.
  • 9. Eldessouki M, Hassan M. 2015. Adaptive neuro-fuzzy system for quantitative evaluation of woven fabrics pilling resistance. Expert Systems with Applications 42(4), 2098-2113.
  • 10. Zhang J, Wang X, Palmer S. 2007. Objective grading of fabric pilling with wavelet texture analysis. Textile Research Journal 77(11), 871-879.
  • 11. Eldessouki M, Bukhari HA, Hassan M, Qashqary K. 2014. Integrated computer vision and soft computing system for classifying the pilling resistance of knitted fabrics. Fibres & Textiles in Eastern Europe.
  • 12. Techniková L, Tunák M, Janáček J. 2017. New objective system of pilling evaluation for various types of fabrics. The Journal of The Textile Institute, 108(1), 123-131.
  • 13. Konda A, Xin LC, Takadera M, Okoshi Y, Toriumi K. 1990. Evaluation of pilling by computer image analysis. Journal of the Textile Machinery Society of Japan, 36(3), 96-107.
  • 14. Xu B. 1997. Instrumental evaluation of fabric pilling. The Journal of the Textile Institute, 88(4), 488-500.
  • 15. Hsi CH, Bresee RR, Annis PA. 1998. Characterizing fabric pilling by using image-analysis techniques. Part II: Comparison with visual pill ratings. Journal of the Textile Institute, 89(1), 96-105.
  • 16. Abril HC, Garcia-Verela MSM, Moreno YMT, Navarro RF. 1998. Automatic method based on image analysis for pilling evaluation in fabrics. Optical Engineering, 37(11), 2937-2948.
  • 17. Kang TJ, Cho DH, Kim SM. 2004. Objective evaluation of fabric pilling using stereovision. Textile research journal 74(11), 1013-1017.
  • 18. Kim SC, Kang TJ. 2005. Image analysis of standard pilling photographs using wavelet reconstruction. Textile Research Journal 75(12), 801-811.
  • 19. Behera BK, Madan Mohan TE. 2005. Objective measurement of pilling by image processing technique. International Journal of Clothing Science and Technology 17(5), 279-291.
  • 20. Zhang J, Wang X, Palmer S. 2007. Objective pilling evaluation of wool fabrics. Textile Research Journal 77(12), 929-936.
  • 21. Telli A, Özkan İ. 2018, October. The Objective Evaluation of Pilling Tendency of Knitted Fabrics Through Digital Image Processing, ITTC- 7th International Technical Textiles Congress. 309-312.
  • 22. Telli A, Özkan İ. 2018. Objective Measurement of Pilling Resistance in Knitted Fabrics with Image Processing Techniques. Journal of Textiles and Engineer 25(112), 313-318.
  • 23. Xin B, Hu J, Yan H. 2002. Objective evaluation of fabric pilling using image analysis techniques. Textile Research Journal 72(12), 1057-1064.
Year 2019, Volume: 29 Issue: 3, 268 - 276, 30.09.2019
https://doi.org/10.32710/tekstilvekonfeksiyon.621184

Abstract

References

  • 1. Ukponmwan JO, Mukhopadhyay A, Chatterjee KN. 1998. Pilling. Textile progress 28(3), 1-57.
  • 2. Özdil N. 2003. Kumaşlarda fiziksel kalite kontrol yöntemleri, E.Ü. Tekstil ve Konfeksiyon Araştırma Uygulama Merkezi Yayınları Yayın No: 21, ISBN No: 975-483-579-9, Bornova-İzmir, 120s.
  • 3. Özçelik G. 2009. Kumaş boncuklanma özelliğinin objektif olarak değerlendirilmesi ve tahminlenmesi üzerine bir araştırma, E.Ü. Fen Bilimleri Enstitüsü Doktora Tezi, Bornova-İzmir, 291s.
  • 4. Kayseri GÖ, Kirtay E. 2015. Part 1. Predicting the pilling tendency of the cotton interlock knitted fabrics by regression analysis. Journal of Engineered Fibers and Fabrics 10(3), 155892501501000305.
  • 5. Kayseri GÖ, Kirtay E. 2015. Part II. Predicting the pilling tendency of the cotton interlock knitted fabrics by artificial neural network. Journal of Engineered Fibers and Fabrics 10(4), 155892501501000417.
  • 6. Telli A. 2015, April. The reliability of subjective assessment in the determination of pilling resistance of knitted fabrics, 4th International Mediterranean Science and Engineering Congress (IMSEC 2019), 420-422.
  • 7. Furferi R, Governi L, Volpe Y. 2015. Machine vision-based pilling assessment: a review. Journal of Engineered Fibers and Fabrics 10(3), 155892501501000320.
  • 8. Wong C. (Ed.). 2017. Applications of Computer Vision in Fashion and Textiles. Woodhead Publishing.
  • 9. Eldessouki M, Hassan M. 2015. Adaptive neuro-fuzzy system for quantitative evaluation of woven fabrics pilling resistance. Expert Systems with Applications 42(4), 2098-2113.
  • 10. Zhang J, Wang X, Palmer S. 2007. Objective grading of fabric pilling with wavelet texture analysis. Textile Research Journal 77(11), 871-879.
  • 11. Eldessouki M, Bukhari HA, Hassan M, Qashqary K. 2014. Integrated computer vision and soft computing system for classifying the pilling resistance of knitted fabrics. Fibres & Textiles in Eastern Europe.
  • 12. Techniková L, Tunák M, Janáček J. 2017. New objective system of pilling evaluation for various types of fabrics. The Journal of The Textile Institute, 108(1), 123-131.
  • 13. Konda A, Xin LC, Takadera M, Okoshi Y, Toriumi K. 1990. Evaluation of pilling by computer image analysis. Journal of the Textile Machinery Society of Japan, 36(3), 96-107.
  • 14. Xu B. 1997. Instrumental evaluation of fabric pilling. The Journal of the Textile Institute, 88(4), 488-500.
  • 15. Hsi CH, Bresee RR, Annis PA. 1998. Characterizing fabric pilling by using image-analysis techniques. Part II: Comparison with visual pill ratings. Journal of the Textile Institute, 89(1), 96-105.
  • 16. Abril HC, Garcia-Verela MSM, Moreno YMT, Navarro RF. 1998. Automatic method based on image analysis for pilling evaluation in fabrics. Optical Engineering, 37(11), 2937-2948.
  • 17. Kang TJ, Cho DH, Kim SM. 2004. Objective evaluation of fabric pilling using stereovision. Textile research journal 74(11), 1013-1017.
  • 18. Kim SC, Kang TJ. 2005. Image analysis of standard pilling photographs using wavelet reconstruction. Textile Research Journal 75(12), 801-811.
  • 19. Behera BK, Madan Mohan TE. 2005. Objective measurement of pilling by image processing technique. International Journal of Clothing Science and Technology 17(5), 279-291.
  • 20. Zhang J, Wang X, Palmer S. 2007. Objective pilling evaluation of wool fabrics. Textile Research Journal 77(12), 929-936.
  • 21. Telli A, Özkan İ. 2018, October. The Objective Evaluation of Pilling Tendency of Knitted Fabrics Through Digital Image Processing, ITTC- 7th International Technical Textiles Congress. 309-312.
  • 22. Telli A, Özkan İ. 2018. Objective Measurement of Pilling Resistance in Knitted Fabrics with Image Processing Techniques. Journal of Textiles and Engineer 25(112), 313-318.
  • 23. Xin B, Hu J, Yan H. 2002. Objective evaluation of fabric pilling using image analysis techniques. Textile Research Journal 72(12), 1057-1064.
There are 23 citations in total.

Details

Primary Language English
Subjects Wearable Materials
Journal Section Articles
Authors

Abdurrahman Telli

Publication Date September 30, 2019
Submission Date March 29, 2019
Acceptance Date September 3, 2019
Published in Issue Year 2019 Volume: 29 Issue: 3

Cite

APA Telli, A. (2019). AN IMAGE PROCESSING RESEARCH CONSISTENT WITH STANDARD PHOTOGRAPHS TO DETERMINE PILLING GRADE OF WOVEN FABRICS. Textile and Apparel, 29(3), 268-276. https://doi.org/10.32710/tekstilvekonfeksiyon.621184

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