In this paper, a computerized method has been proposed for automatic measurement and recognition of yarn wet snarls from an image of snarled yarn samples captured in a water bath. After image acquisition, image conversion and individual snarled sample extraction, the yarn profile function was extracted from the separated binary image. Fast Fourier Transform and Adaptive Orientated Orthogonal Projective Decomposition were then incorporated into a pattern recognition algorithm of yarn snarl features by treating the yarn profile function as a one-dimensional signal. In addition to the number of yarn snarl turns, the method was also accurate and efficient for the detection of yarn snarl height and width, which are unobtainable by the untwisting method. The effects of various factors on the yarn profile function were numerically examined, including distributions of yarn diameter and snarl, and the level of random noise.
Belov, E.B., Lomov, S.V., Truevtsev, N.N., Bradshaw, M.S., and Harwood, R.J., Study of Yarn Snarling - Part I: Critical Parameters of Snarling, J. Textile Inst. 93(4), 341-364 (2002).
2.
Murrells, C.M. , Wong, K.K., Tao , X.M., and Xu , B.G., Yarn Snarling Testing Apparatus and Method, U.S. Patent 7,219, 556 B2 (2007).
3.
Murrells, C.M. , Wong, K.K., Hua , T., Leung, C.L., Xu , B.G., Yang, K., Wong, S.K., Cheng, K.P.S., and Tao , X.M., Study of Yarn Snarling in Nu-torque™ Singles Ring Yarns, in "Proceedings of the Textile Institute 83rd World Conference," Shanghai , China, pp. 401-404 (2004).
4.
Kim, S.C. , and Kang, T.J., Fabric Surface RoughnessEvaluation Using Wavelet-fractalMethod: Part II: Fabric Pilling Evaluation, Textile Res. J . 75(11), 761-770 (2005).
5.
Kim, S.C. , and Kang, T.J., Image Analysis of Standard Pilling Photographs Using Wavelet Reconstruction, Textile Res. J. 75(12), 801-811 (2005).
6.
Palmer, S., and Wang, X.G., Objective Classification of Fabric Pilling Based on the Two-dimensional Discrete Wavelet Transform, Textile Res. J. 73(8), 713-720 (2003).
7.
Palmer, S., and Wang, X.G., Evaluating the Robustness of Objective Pilling Classification with the Two-dimensional Discrete Wavelet Transform, Textile Res. J. 74(2), 140-145 (2004).
8.
Sirikasemlert, A., and Tao, X.M., Objective Evaluation of Textural Changes in Knitted Fabrics by Laser Triangulation, Textile Res. J . 70(12), 1076-1087 (2000 ).
9.
Kuo, C.-F.J. , and Tsai, C.C., Automatic Recognition of Fabric Nature by Using the Approach of Texture Analysis, Textile Res. J.76(5), 375-382 (2006).
10.
Kang, T.J., Kim, S.C., Sul, I.H., Youn, J.R., and Chung, K., Fabric Surface RoughnessEvaluation Using Wavelet-fractalMethod: Part I: Wrinkle, Smoothness and Seam Pucker, Textile Res. J. 75(11), 751-760 (2005).
11.
Cardamone, J.M., Damert, W.C., Phillips , J.G., and Marmer, W.N., Digital Image Analysis for Fabric Assessment , Textile Res. J. 72(10), 906-916 (2002).
12.
Shady, E., Gowayed, Y., Abouiiana, M., Youssef, S., and Pastore, C., Detection and Classification of Defects in Knitted Fabric Structures , Textile Res. J. 76(4), 295-300 (2006).
13.
Kuo, C.-F.J. , and Su, T.L., Gray Relational Analysis for Recognizing Fabric Defects, Textile Res. J.73(5), 461-465 (2003).
14.
Jeong, S.H. , Choi, H.T., Kim , S.R., Jaung, J.Y., and Kim , S.H., Detecting Fabric Defects with Computer Vision and Fuzzy Rule Generation Part I: Defect Classification by Image Processing , Textile Res. J. 71(6), 518-526 (2001).
15.
Saeidi, R.G. , Latifi, M., Najar , S.S., and Saeidi, A.G., Computer Vision-aided Fabric Inspection System for On-circular Knitting Machine, Textile Res. J. 75(6), 492-497 (2005).
16.
Ucar, N., Kalaoclu, F., Bahtiyar, D., and Blac, O.E., Investigating the Drape Behavior of Seamed Knit Fabrics with Image Analysis , Textile Res. J. 74(2), 166-171 (2004).
17.
Robson, D., and Long, C.C., Drape Analysis Using Imaging Techniques, Clothing Textiles Res. J.18(1), 1-8 (2000).
18.
Huang, Y., and Xu, B., Image Analysis for Cotton Fibers: Part I: Longitudinal Measurements , Textile Res. J. 72(8), 713-720 (2002).
19.
Xu, B., and Huang, Y., Image Analysis for Cotton Fibers Part II: Cross-sectional Measurements , Textile Res. J. 74(5), 409- 416 (2004).
20.
Semnani, D. , Latifi, M., Tehran , M.A., Pourdeyhimi, B., and Merati, A.A., Grading of Yarn Appearance Using Image Analysis and an Artificial Intelligence Technique, Textile Res. J. 76(3), 187-196 (2006).
21.
Otsu, N., A Threshold Selection Method from Gray-level Histograms, IEEE Trans. Syst. Man Cybern. 9(1), 62-66 (1979).
22.
Haralick, R.M. , and Shapiro, L.G., "Computer and Robot Vision," Vol. I, Addison-Wesley, Reading, MA, USA, pp. 28- 48 (1992).
23.
Smith, J.O., III, "Mathematics of the Discrete Fourier Transform (DFT) - with Audio Applications," W3K Publishing Stanford, CA , USA, (2003).
24.
Grandke, T. , Interpolation Algorithms for Discrete Fourier-transforms of Weighted Signals, IEEE Trans. Instrum. Meas. 32(2), 350-355 (1983).
25.
Bultan, A., A Four-parameter Atomic Decomposition of Chirplets, IEEE Trans. Signal Process. 47(3), 731-745 (1999).
26.
Yin, Q. , Qian, S., and Feng, A., A Fast Refinement for Adaptive Gaussian Chirplet Decomposition, IEEE Trans. Signal Process. 50(6), 1298-1306 (2002).
27.
Qian, S., and Chen, D., Signal Representation Using Adaptive Normalized Gaussian Functions , Signal Process.36(1), 1-11 (1994).
28.
Qian, S., "Introduction to Time-frequency and Wavelet Transforms," Prentice-HallNJ, USA, (2002).
