305
Views
8
CrossRef citations to date
0
Altmetric
Articles

Weave pattern recognition by measuring fiber orientation with Fourier transform

, , &
Pages 622-630 | Received 20 Dec 2015, Accepted 07 Apr 2016, Published online: 17 May 2016

References

  • Ben Salem, Y., & Nasri, S. (2010). Automatic recognition of woven fabrics based on texture and using SVM. Signal, Image and Video Processing, 4, 429–434. doi: 10.1007/s11760-009-0132-5
  • Cleveland, W. S. (1979). Robust locally weighted regression and smoothing scatterplots. Journal of the American Statistical Association, 74(368), 829–836.
  • Cleveland, W. S. (1981). LOWESS: a program for smoothing scatterplots by robust locally weighted regression. The American Statistician, 35(1), 54.
  • Illingworth, J., & Kittler, J. (1988). A survey of the Hough transform. Computer Vision, Graphics, and Image Processing, 44, 87–116. doi:10.1016/S0734-189X(88)80033-1
  • Jain, A. K. (2010). Data clustering: 50 years beyond K-means. Pattern Recognition Letters, 31, 651–666. doi:10.1016/j.patrec.2009.09.011
  • Jeong, Y. J., & Jang, J. H. (2005). Applying image analysis to automatic inspection of fabric density for woven fabrics. Fibers and Polymers, 6, 156–161. doi:10.1007/BF02875608
  • Jing, J. F., Xu, M. M., Li, P. F., Li, Q., & Liu, S. M. (2014). Automatic classification of woven fabric structure based on texture feature and PNN. Fibers and Polymers, 15, 1092–1098. doi:10.1007/s12221-014-1092-0
  • Kang, T. J., Kim, C. H., & Oh, K. W. (1999). Automatic Recognition of Fabric Weave Patterns by Digital Image Analysis. Textile Research Journal, 69, 77–83. doi:10.1177/004051759906900201
  • Kuo, C. F. J., Shih, C. Y., Ho, C. E., & Peng, K. C. (2010). Application of computer vision in the automatic identification and classification of woven fabric weave patterns. Textile Research Journal, 80, 2144–2157. doi:10.1177/0040517510373630
  • Kuo, C. F. J., Shih, C. Y., & Lee, J. Y. (2004). Automatic recognition of fabric weave patterns by a fuzzy C-means clustering method. Textile Research Journal, 74, 107–111. doi:10.1177/004051750407400204
  • Kuo, C. F. J., & Tsai, C. C. (2006). Automatic recognition of fabric nature by using the approach of texture analysis. Textile Research Journal, 76, 375–382. doi:10.1177/0040517506063917
  • 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, 179–183. doi:10.1533/joti.2004.0069
  • 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 crossed-points detection. The Journal of The Textile Institute, 94, 194–201. doi:10.1080/00405000308630608
  • Lin, J. J. (2002). Applying a co-occurrence matrix to automatic inspection of weaving density for woven fabrics. Textile Research Journal, 72, 486–490. doi:10.1177/004051750207200604
  • Marquez, J. P. (2006). Fourier analysis and automated measurement of cell and fiber angular orientation distributions. International Journal of Solids and Structures, 43, 6413–6423. doi:10.1016/j.ijsolstr.2005.11.003
  • Pan, R. R., Gao, W. D., Liu, J. H., & Wang, H. B. (2010). Automatic recognition of woven fabric patterns based on pattern database. Fibers and Polymers, 11, 303–308. doi:10.1007/s12221-010-0303-6
  • Pan, R. R., Gao, W. D., Liu, J. H., & Wang, H. B. (2010). Automatic inspection of woven fabric density of solid colour fabric density by the Hough transform. Fibres and Textile in Eastern Europe, 18, 46–51.
  • Pan, R. R., Gao, W. D., Liu, J. H., & Wang, H. B. (2011). Automatic recognition of woven fabric pattern based on image processing and BP neural network. The Journal of The Textile Institute, 102, 19–30. doi:10.1080/00405000903430255
  • Pan, R. R., Gao, W. D., Liu, J. H., Wang, H. B., & Qian, X. X. (2011). Automatic inspection of double-system-mélange yarn-dyed fabric density with color-gradient image. Fibers and Polymers, 12, 127–131.10.1007/s12221-011-0127-z
  • Pan, R. 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. R., Liu, J. H., & Gao, W. D. (2013). Measuring linear density of threads in single-system-mélange color fabrics with FCM algorithm. Color Research & Application, 38, 456–462. doi:10.1002/col.21738
  • Ravandi, S. A. H., & Toriumi, K. (1995). Fourier-transform analysis of plain weave fabric appearance. Textile Research Journal, 65, 676–683. doi:10.1177/004051759506501108
  • Sander, E. A., & Barocas, V. H. (2009). Comparison of 2D fiber network orientation measurement methods. Journal of Biomedical Materials Research Part A, 88A, 322–331. doi:10.1002/jbm.a.31847
  • Schneider, D., & Merhof, D. (2015). Blind weave detection for woven fabrics. Pattern Analysis and Applications. 18(3), 725–737. doi: 10.1007/s10044-014-0403-9
  • Technikova, L., & Tunak, M. (2013). Weaving density evaluation with the aid of image analysis. Fibres and Textile in Eastern Europe, 21, 74–79.
  • Tunak, M., & Linka, A. (2007). Analysis of planar anisotropy of fibre systems by using 2D Fourier transform. Fibres and Textile in Eastern Europe, 15, 86–90.
  • Tunak, M., Linka, A., & Volf, P. (2009). Automatic assessing and monitoring of weaving density. Fibers and Polymers, 10, 830–836. doi: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
  • Xiao, Z. T., Nie, X. X., Zhang, F., & Geng, L. (2014). Recognition for woven fabric pattern based on gradient histogram. The Journal of The Textile Institute, 105, 744–752. doi:10.1080/00405000.2013.847542
  • Xiao, Y., & Yu, J. (2012). Partitive clustering (K-means family). Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 2, 209–225. doi:10.1002/Widm.1049
  • 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
  • Zhang, J, Pan, R., & Gao, D. (2015). Automatic inspection of the density in yarn-dyed fabric by utilizing fabric light transmittance and Fourier analysis. Applied Optics (ahead-of-print). doi: 10.1364/AO.54.000966
  • Zhang J, Pan R., Gao W., & Zhu, D. (2015). Automatic detection of layout of color yarns of yarn-dyed fabric. Part 1: Single-system-mélange color fabrics. Color Research & Application, 40(6), 626–636.
  • Zhang, J., Pan, R., Gao, W., & Zhu, D. (2015). Automatic inspection of yarn-dyed fabric density by mathematical statistics of sub-images. The Journal of The Textile Institute, 106(8), 823–834.
  • 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(11), 115007–110233.
  • 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
  • Zhong, P., Ye, T., Shi, Y. L., & Tu, X. X. (2013). Research on computer-aided analysis and reverse reconstruction for the weave pattern of fabric. Textile Research Journal, 83, 298–310. doi:10.1177/0040517512460302
  • Zhou, D., Zhou, L. Q., & Sun, J. (2015). A novel feedback error-correcting algorithm for automatic recognition of the color and weave pattern of yarn-dyed fabrics. Text Res J, 83, 1673–1689. doi:10.1177/0040517513481866

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.