388
Views
10
CrossRef citations to date
0
Altmetric
Articles

A computer vision-based system for automatic detection of misarranged warp yarns in yarn-dyed fabric. Part I: continuous segmentation of warp yarns

ORCID Icon, , , &
Pages 577-584 | Received 15 Feb 2017, Accepted 25 Jul 2017, Published online: 06 Aug 2017

References

  • Bay, H., Ess, A., Tuytelaars, T., & Van Gool, L. (2008). Speeded-Up Robust Features (SURF). Computer Vision and Image Understanding, 110, 346–359.10.1016/j.cviu.2007.09.014
  • Bay, H., Tuytelaars, T., & Van Gool, L. (2006). SURF: Speeded up robust features. Computer Vision – Eccv 2006, Pt 1, Proceedings, 3951, 404–417.
  • Lewis, J. (1995). Fast normalized cross-correlation In Vision interface 10, 120–123.
  • Li, S. Y., Xu, B. G., Tao, X. M., & Chi, Z. R. (2015). An intelligent computer method for automatic mosaic and segmentation of tracer fiber images for yarn structure analysis. Textile Research Journal, 85, 733–750. doi:10.1177/0040517514551459
  • Liu, S., & Xia, L. (2010). A kind of method for fabric image mosaic (pp. 668–671).
  • Lowe, D. G. (2004). Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision, 60, 91–110.10.1023/B:VISI.0000029664.99615.94
  • Luo, L., Shen, H. L., Shao, S. J., & Xin, J. H. (2015). An efficient method for solid-colour and multicolour region segmentation in real yarn-dyed fabric images. Coloration Technology, 131, 120–130. doi:10.1111/cote.12131
  • Pan, R. R., Gao, W. D., Liu, J. H., & Wang, H. B. (2010a). Automatic detection of the layout of color yarns for yarn-dyed fabric via a FCM algorithm. Textile Research Journal, 80, 1222–1231. doi:10.1177/0040517509355349
  • Pan, R. R., Gao, W. D., Liu, J. H., & Wang, H. B. (2010b). Automatic inspection of woven fabric density of solid colour fabric density by the hough transform. Fibres & Textiles in Eastern Europe, 18, 46–51.
  • Pan, R. R., Gao, W. D., Liu, J. H., Wang, H. B., & Qian, X. X. (2011). Automatic inspection of double-system-melange Yarn-dyed fabric density with color-gradient image. Fibers and Polymers, 12, 127–131. doi:10.1007/s12221-011-0127-z
  • Pan, R., Gao, W. D., Liu, J. H., Wang, H. B., & Zhang, X. T. (2010). Automatic detection of structure parameters of yarn-dyed fabric. Textile Research Journal, 80, 1819–1832. doi:10.1177/0040517510369411
  • Pan, R., Liu, J., & Gao, W. (2013). Measuring linear density of threads in single-system-mélange color fabrics with FCM algorithm. Color Research & Application, 38, 456–462.
  • Rahul, S., & Yan, K. (2004). PCA-SIFT: A more distinctive representation for local image descriptors (pp. 506–513).
  • Schneider, A. D. (2013). Tracking yarns in high resolution fabric images: A real-time approach for online fabric flaw detection. Is & T/spie Electronic Imaging, 8656, 759–767.
  • Schneider, D., Gloy, Y. S., & Merhof, D. (2015). Vision-based on-loom measurement of yarn densities in woven fabrics. IEEE Transactions on Instrumentation and Measurement, 64, 1063–1074.10.1109/TIM.2014.2363580
  • Schneider, D., & Merhof, D. (2015). Blind weave detection for woven fabrics. Pattern Analysis and Applications, 18, 725–737.10.1007/s10044-014-0403-9
  • Technikova, L., & Tunak, M. (2013). Weaving density evaluation with the aid of image analysis. Fibres & Textiles in Eastern Europe, 21, 74–79.
  • Tunak, M., Linka, A., & Volf, P. (2009). Automatic assessing and monitoring of weaving density. Fibers and Polymers, 10, 830–836.10.1007/s12221-009-0830-1
  • Wang, X., Georganas, N. D., & Petriu, E. M. (2011). Fabric texture analysis using computer vision techniques. IEEE Transactions on Instrumentation and Measurement, 60, 44–56. doi:10.1109/Tim.2010.2069850
  • Wang, X. C., & Li, X. J. (2012). Recognition of fabric density with quadratic local extremum. International Journal of Clothing Science and Technology, 24, 328–338. doi:10.1108/09556221211258993
  • Xin, B. J., Hu, J. L., Baciu, G., & Yu, X. B. (2009). Investigation on the classification of weave pattern based on an active grid model. Textile Research Journal, 79, 1123–1134. doi:10.1177/0040517508101459
  • Xu, B. G. (1996). Identifying fabric structures with fast Fourier transform techniques. Textile Research Journal, 66, 496–506.
  • Zhang, J., Pan, R., & Gao, W. (2015). Automatic inspection of density in yarn-dyed fabrics by utilizing fabric light transmittance and Fourier analysis. Applied Optics, 54, 966–972.10.1364/AO.54.000966
  • Zhang, J., Pan, R., Gao, W., & Zhu, D. (2014a). Automatic detection of layout of color yarns of yarn-dyed fabric. Part 1: Single-system-mélange color fabrics. Color Research & Application, 40, 626–636, 2015.
  • Zhang, J., Pan, R., Gao, W., & Zhu, D. (2014b). Automatic inspection of yarn-dyed fabric density by mathematical statistics of sub-images. The Journal of The Textile Institute, 106, 823–834, 2015.
  • Zhang, J., Pan, R., Gao, W., & Zhu, D. (2014c). Automatic recognition of the color effect of yarn-dyed fabric by the smallest repeat unit recognition algorithm. Textile Research Journal, 85, 432–446, 2015.
  • Zhang, J., Xin, B., & Wu, X. (2014). Density measurement of yarn dyed woven fabrics based on dual-side scanning and the FFT technique. Measurement Science and Technology, 25, 115007.
  • Zheng, D. J., Han, Y., & Hu, J. L. (2014). A new method for classification of woven structure for yarn-dyed fabric. Textile Research Journal, 84, 78–95. doi:10.1177/0040517513483858
  • Zhou, D., Zhou, L. Q., & Sun, J. (2013). A novel feedback error-correcting algorithm for automatic recognition of the color and weave pattern of yarn-dyed fabrics. Textile Research Journal, 83, 1673–1689.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.