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http://dx.doi.org/10.3837/tiis.2020.02.012

A Sobel Operator Combined with Patch Statistics Algorithm for Fabric Defect Detection  

Jiang, Jiein (School of Computer and Software, Nanjing University of Information Science and Technology)
Jin, Zilong (School of Computer and Software, Nanjing University of Information Science and Technology)
Wang, Boheng (School of Computer and Software, Nanjing University of Information Science and Technology)
Ma, Li (School of Computer and Software, Nanjing University of Information Science and Technology)
Cui, Yan (College of Mathematics and Information Science, Nanjing Normal University of Special Education)
Publication Information
KSII Transactions on Internet and Information Systems (TIIS) / v.14, no.2, 2020 , pp. 687-701 More about this Journal
Abstract
In the production of industrial fabric, it needs automatic real-time system to detect defects on the fabric for assuring the defect-free products flow to the market. At present, many visual-based methods are designed for detecting the fabric defects, but they usually lead to high false alarm. Base on this reason, we propose a Sobel operator combined with patch statistics (SOPS) algorithm for defects detection. First, we describe the defect detection model. mean filter is applied to preprocess the acquired image. Then, Sobel operator (SO) is applied to deal with the defect image, and we can get a coarse binary image. Finally, the binary image can be divided into many patches. For a given patch, a threshold is used to decide whether the patch is defect-free or not. Finally, a new image will be reconstructed, and we did a loop for the reconstructed image to suppress defects noise. Experiments show that the proposed SOPS algorithm is effective.
Keywords
Mean filter; Sobel operator; Patch statistics; Spectral approaches; Wavelet transform;
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1 P.M. Mahajan, S.R. Kolhe, P.M. Pati, "A review of automatic fabric defect detection techniques," Adv. Comput. Res, vol. 127, no. 2, pp. 18-29, 2009.
2 K. Hanbay, M. F. Talu, O.F. Ozguven, "Fabric defect detection systems and methods-A systematic literature review," Optik, vol. 127, pp. 11960-11973, 2016.   DOI
3 J. Chen, A.K. Jain, "A structural Approach to Identify Defects in Textured Images," in Proc. of IEEE Int'l Conf. Systems, Man & Cybernetics, pp. 29-32, 1988.
4 R.M. Haralick, K. Shanmugam, I. Dinstein, "Textural features for image classification," IEEE Trans. Systems, Man and Cybernetics, vol. 3, no. 6, pp. 610-621, 1973.   DOI
5 YF. Zhang, RR. Bresee, "Fabric defect detection and classification using image analysis," Text Res J, vol. 65, no. 1, pp. 1-9, 1995.   DOI
6 K. Hoshino, H. Sumi, T. Nishimura, "Noise detection and reduction for image sensor by time domain auto correlation function method," in Proc. of IEEE International Symposium on Industrial Electronics, pp. 1737-1740, 2007.
7 D. Wang, H. Liu, "Edge detection of cord fabric defects image based on an improved morphological erosion detection methods," in Proc. of Sixth International Conference on Natural Computation (ICNC), pp. 3943-3947, 2010.
8 V. Jayashree, S. Subbaramn, "Hybrid Approach using correlation and morphological approaches for GFDD of plain weave fabric," IEEE Control and System Graduate Research Colloquium, pp. 197-202, 2012.
9 V.V. Karlekar, M.S. Biradar, K.B. Bhangale, "Fabric defect detection using wavelet Filter," in Proc. of International Conference on Computing Communication Control and Automation (ICCUBEA), pp. 712-715, 2015.
10 A. Kumar, G.K.H. Pang, "Defect detection in textured materials using Gabor filters," IEEE Trans. Industry Applications, vol. 38, no. 2, pp. 425-440, 2002.   DOI
11 Y. Zhang, Z. Lu, J. Li, "Fabric defect detection and classification using Gabor filters and Gaussian mixture model," in Proc. of Asian Conference on Computer Vision-accv, pp. 635-644, 2009.
12 L. Tong, W. K Wong, C. K. Kwong, "Differential evolution-based optimal Gabor filter model for fabric inspection," Neurocomput., vol. 173, pp. 1386-1401, 2016.   DOI
13 L. Jia, C. Chen, L. Jiang, Z. Hou. "Fabric defect inspection based on lattice segmentation and Gabor filtering," Neurocomput., vol. 238, pp. 84-102, 2017.   DOI
14 K. Sakhare, A. Kulkarni, M. Kumbhakarn, N. Kare, "Spectral and spatial domain approach for fabric defect detection and classification," in Proc. of International Conference on Industrial Instrumentation and Control (ICIC), pp. 640-644, 2015.
15 XZ. Yang, GKH. Pang, NHC. Yung, "Discriminative fabric defect detection using adaptive wavelets," Opt Eng, vol. 41, no. 12, pp. 3116-3126, 2002.   DOI
16 Y. Han, P. Shi, "An adaptive level-selecting wavelet transform for texture defect detection," Image Vision Comput., vol. 25, no. 8, pp. 1239-1248, 2007.   DOI
17 H. Y. Ngan, G. K. Pang, S. Yung, M. K. Ng, "Wavelet based methods on patterned fabric defect detection," Pattern Recognition, vol. 38, no. 4, pp. 559-576, 2005.   DOI
18 CH. Chan, G. Pang, "Fabric defect detection by Fourier analysis," IEEE Transactions on Industry Applications, vol. 36, no. 5, pp. 1267-1276, 2000.   DOI
19 N. Ismail, W.M. Syahrir, J.M. Zain, T. Hai, "Fabric authenticity method using fast Fourier transformation detection," in Proc. of International Conference on Electrical, Control and Computer Engineering (INECCE), pp. 233-237, 2011.
20 D.-M. Tsai and C.-Y. Heish, "Automated surface inspection for directional textures," Image and Vision Computing, vol. 18, pp. 49-62, 1999.   DOI
21 S. Ozdemir, A. Ercil, "Markov random fields and Karhunen-Loeve transform for defect inspection of textile products," in Proc. of IEEE Conference on Emerging Technologies & Factory Automation, pp. 697-703, 1996.
22 J. Jiang, Yan Cui, Y. Chen, G. Gao, "A novel nonlocal low rank technique for fabric defect detection," in Proc. of The 4th International Conference on Cloud Computing and Security, pp. 173-182, 2018.
23 O. Alata, C. Ramananjarasoa, "Unsupervised textured image segmentation using 2-D quarter plan autoregressive model with four prediction supports," Pat. Rec.Lett., vol. 26, no. 8, pp. 1069-1081, 2005.   DOI
24 J. Zhou, D. Semenovich, A. Sowmya, J. Wang, "Dictionary learning framework for fabric defect detection," The Journal of the Textile Institute, vol. 105, no. 3, pp. 223-234, 2014.   DOI
25 L. Tong, W. K Wong, C. K. Kwong, "Fabric defect detection for apparel industry: a nonlocal sparse representation approach," IEEE Access, vol. 5, pp. 5947-5964, 2017.   DOI
26 J. Wang, Q. Li, J. Gan, H. Yu, "Fabric defect detection based on improved low-rank and sparse matrix decomposition," in Proc. of The 2017 IEEE International Conference on Image Processing, pp. 2776-2780, 2017.
27 Y. Li, D. Zhang, D-J. Lee, "Automatic fabric defect detection with a wide-and-compact network," Neurocomput., vol. 329, pp. 329-338, 2019.   DOI
28 J. Jiang, Yan Cui, Z. Jin, C. Fan, "Fast three-phase fabric defect detection," in Proc. of The 4th International Conference on Cloud Computing and Security, pp. 302-312, 2018.
29 M Aharon, M Elad and A. Bruckstein, "K-SVD: An algorithm for designing of overcomplete dictionaries for sparse representation," IEEE Trans. Signal Process, vol. 54, no. 11, pp. 4311-4322, 2006.   DOI
30 G. Hu, Q. Wang, G. Zhang, "Unsupervised defect detection in textiles based on Fourier analysis and wavelet shrinkage," Appl. Opt, vol. 54, no. 10, pp. 2963-2980, 2015.   DOI