The use of image processing for the detection and classification of defects has been a reality for some time in science and industry. New methods are continually being presented to improve every aspect of this process. However, these new approaches are applied to a small, private collection of images, which makes a real comparative study of these methods very difficult. The objective of this paper was to compile a public annotated benchmark, that is, an extensive set of images with and without defects, and make these public, to enable the direct comparison of detection and classification methods. Moreover, different methods are reviewed and one of these is applied to the set of images; the results of which are also presented in this paper.
If the inline PDF is not rendering correctly, you can download the PDF file here.
 Kumar, A. (2008). Computer-vision-based fabric defect detection: a survey. IEEE Transactions on Industrial Electronics, 55(1), 348-363.
 Ngan, H. Y., Pang, G. K., Yung, N. H. (2011). Automated fabric defect detection – a review. Image and Vision Computing, 29(7), 442-458.
 Habib, T., Faisal, R., Rokonuzzaman, M., Ahmed, F. (2014). Automated fabric defect inspection: a survey of classifiers. International Journal in Foundations of Computer Science & Technology (IJFCST), 4(1), 17-25.
 Hanbay, K., Talu, M., Özguven, Ö. (2016). Fabric defect detection systems and methods. A systematic literature review. Optik, 127, 11960-11973.
 Goyal, A. (2018). Automation in fabric inspection, in Automation in Garment Manufacturing, Woodhead Publishing, 75-107.
 Hillel, A. B., Lerner, R., Levi, D., Raz, G. (2014). Recent progress in road and lane detection: a survey. Machine Vision and Applications, 25, 727-745.
 Rebhi, A., Benmhammed, I., Abid, S., Fnaiech, F. (2015). Fabric defect detection using local homogeneity analysis and neural network. Journal of Photonics, 2015, 2015.
 ASTM. (2016). Standard Terminology Relating to Fabric Defects. Designation: D 3990 – 12,” ASTM, West Conshohocken.
 Ahmed, A. (2016). A catalogue of visual textile defects. TS3B.
 Sari-Sarraf, H., Goddard, J. S. (1999). Vision system for on-loom fabric inspection. IEEE Transactions on Industry Applications, 35(6), 1252-1259.
 Kumar, A., Pang, G. (2001). Identification of surface defects in textured materials using wavelet packets, in Industry Applications Conference, 2001. Thirty-Sixth IAS Annual Meeting. Conference Record of the 2001 IEEE.
 Wen, C.-Y., Chiu, S.-H., Hsu, W.-S., Hsu, G.-H. (2001). Defect segmentation of texture images with wavelet transform and co-occurrence matrix. Textile Research Journal, 71(8), 743-749.
 Zeng, P., Hirata, T. (2002). On-loom fabric inspection using multi-scale differentiation filtering, in Industry Applications Conference, 37th IAS Annual Meeting. Conference Record of the, Pittsburgh, PA, USA.
 Kumar, A., Pang, G. (2002). Defect detection in textured materials using optimized filters. IEEE Transactions on Systems, Man, and Cybernetics, 32(5), 553-570.
 Yang, X. Z., Pang, G., Yung, N. (2002). Discriminative fabric defect detection using adaptive wavelets. Optical Engineering, 41(12), 3116-3126.
 Shu, Y., Tan, Z. (2004). Fabric defects automatic detection using Gabor filters, in Intelligent Control and Automation, 2004. WCICA 2004. Fifth World Congress on, 2004.
 Murino, V., Bicego, M., Rossi, I. A. (2004). Statistical classification of raw textile defects, in Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on, 2004.
 Cho, C.-S., Chung, B.-M., Park, M.-J. (2005). “Development of real-time vision-based fabric inspection system. IEEE Transactions on Industrial Electronics, 52(4), 1073-1079.
 Mak, K. L., Peng, P., Lau, H. Y. (2005). Optimal morphological filter design for fabric defect detection, in Industrial Technology, 2005. ICIT 2005. IEEE International Conference on, Hong Kong.
 Yang, X., Pang, G., Yung, N. (2005). Robust fabric defect detection and classification using multiple adaptive wavelets. IEEE Proceedings - Vision, Image and Signal Processing, 152(6), 715-723.
 Zhu, S. W., Hao, H. Y., Li, P. Y., Shi, M. H., Qi, H. (2007). Fabric defects segmentation approach based on texture primitive, in Machine Learning and Cybernetics, 2007 International Conference on, 2007.
 Basturk, A., Ketencioglu, H., Yugnak, Z., Yuksel, M. E. (2007). Inspection of defects in fabrics using Gabor wavelets and principle component analysis, in Signal Processing and Its Applications, International Symposium on (ISSPA), Sharjah.
 Liu, S.-G., Qu, P.-G. (2008). Inspection of fabric defects based on wavelet analysis and BP neural network, in Wavelet Analysis and Pattern Recognition, 2008. ICWAPR ‘08. International Conference on, Hong Kong.
 Liu, Z. (2009). Computer testing method of defect feature of fabric, in Test and Measurement, 2009. ICTM ‘09. International Conference on.
 Mak, K., Peng, P., Lau, H. (2005). A real-time computer vision system for detecting defects in textile fabrics, in International Conference on Industrial Technology, Hong-Kong.
 Mak, K. L., Peng, P., (2008). An automated inspection system for textile fabrics based on Gabor filters. Robotics and Computer-Integrated Manufacturing, 24(3), 359-369.
 Mak, K., Peng, P., Yiu, K. (2009). Fabric defect detection using morphological filters. Image and Vision Computing, 27(10), 1585-1592.
 Graniteville Company. (1975). Manual of standard fabric defects in the textile industry.
 Sheng-Wang, L., Li-Wei, G., Chun-Hua, L. (2009). Fabric defects detecting and rank scoring based on Fisher criterion discrimination, in Machine Learning and Cybernetics, 2009 International Conference on, 2009.
 Yin, Y., Lu, W. B., Zhang, K., Jing, L. (2009). Textile flaw detection and classification by wavelet reconstruction and BP neural network, in Intelligent Systems, 2009. GCIS ‘09. WRI Global Congress on, Xiamen.
 Fan, L., Jiang, G. (2010). Optimized Gabor filter parameters for uniform texture flaw detection, in Intelligent Systems and Knowledge Engineering (ISKE), 2010 International Conference on, Hangzhou.
 Bu, H. G., Huang, X. B., Wang, J., Chen, X. (2010). Detection of fabric defects by auto-regressive spectral analyis and support vector data description. Textile Research Journal, 89(7), 579-589.
 Mingde, B., Zhigang, S., Yesong, L. (2012). Textural fabric defect detection using adaptative quantized gray-level cooccurrence matrix and support vector description data. Information Technology Journal, 11, 673-685.
 Si, X., Zheng, H., Hu, X. (2012). Fabric defect detection based on regional growing PCNN. Journal of Multimedia, 7(5), p. 372.
 Karlekar, V. V., Biradar, M. S., Bhangale, K. B. (2015). Fabric defect detection using wavelet filter, in Computing Communication Control and Automation (ICCUBEA), 2015 International Conference on, Pune.
 Li, Y., Zhang, C. (2016). Automated vision system for fabric defect inspection using Gabor filteres and PCNN. SpringerPlus, 5(1).
 Kumbhar, P., Mathpati, T., Kamaraddi, R., Kshirsagar, N. (2016). Textile fabric defects detection and sorting using image processing. International Journal for Research Emerging Science and Technology, 3(3), 19-24.
 Seker, A., Peker, K., Yüksek, A. D. E. (2016). Fabric defect detection using deep learning, in 24th Signal Processing and Communication Application Conference (SIU), Zonguldak.
 Tong, L., Wong, W., Kwong, C. (2017). Fabric defect detection for apparel industry: a nonlocal sparse representation approach. IEEE Access, 5, 5947-5964.
 Dana, K., Van-Ginneken, B., Nayar, S., Koenderink, J. (1999). Reflectance and texture of real world surfaces. ACM Transactions on Graphics (TOG), 18(1), 1-34.
 Tajeripour, F., Kabier, E., Sheikhi, A. (2008). Fabric defect detection using modified local binary patterns. EURASIP Journal on Advances in Signal Processing, 2008, 60.
 Ngan, H. Y., Pang, G. K., Yung, S., Ng, M. K. (2005). Wavelet based methods on patterned fabric defect detection. Pattern Recognition, 38(4), 559-576.
 Ngan, H. Y., Pang, G. (2009). Regularity analysis for patterned texture inspection. IEEE Transactions on Automation Science and Engineering, 6(1), 131-144.
 Tiwari, V., Sharma, G. (2015). Automatic fabric fault detection using morphological operations on bit plane. IJCSNS International Journal of Computer Science and Network Security, 5(10), 30-35.
 Conci, A., Proença, C. B. (1998). A fractal image analysis system for fabric inspection based on a box-counting method. Computer Networks and Systems, 30(20-21), 1887-1895.
 Huang, F. C., Huang, S. Y., Ker, J. W., Chen, Y. C. (2012). High-performance SIFT hardware accelerator of real-time image feature extraction. IEEE Transactions on Circuits and Systems for Video Technology, 22(3), 340-351.
 Bay, H., Ess, A., Tuytelaars, T., Van Gool, L. (2008). Sepeeded-up robust features (SURF). Computer Vision and Image Understanding, 110(3), 346-359.
 Bissi, L., Baruffa, G., Placid, P., Ricci, E., Scorzon, A., Valigi, P. (2013). Automated defect detection in uniform and structured fabrics using Gabor filters and PCA. Journal of Visual Communication and Image Representation, 24(7), 1047-3203.
 Chen, J., Pappas, T. N., Mojsilovic, A., Rogowitz, B. E. (2005). Adaptive perceptual color-texture image segmentation, in Image Processing, IEEE Transactions on, 2005.
 Chan, C.-H., Pang, G. K. H. (2000). Fabric defect detection by Fourier analysis. IEEE Transactions on Industry Applications, 35(2), 1267-1276.
 Malek, A. S., Drean, J.-Y., Bigue, L., Osselin, J.-F. (2013). Optimization of automated online fabric inspection by fast Fourier Transform (FTT) and cross-correlation. Textile Research Journal, 83(3), 256-268.
 Guang-Hua, H. (2014). Optimal ring Gabor filter design for texture defect detection using a simulated annealing algorithm, in Information Science, Electronics and Electrical Engineering (ISEEE), International Conference on, Sapporo, 2014.
 Han, Y., Shi, P. (2007). An adaptive level-selecting wavelet transform for texture defect detection. Image and Vision Computing, 25(8), 1239-1248.
 Guan, S., Gao, Z. (2014). Fabric defect image segmentation based on the visual attention mechanism of the wavelet domain. Textile Research Journal, 84(10), 1018-1033.
 Mallat, S. (1998). A wavelet tour of signal processing. Academic Press.
 Tsai, D.-M., Hsieh, C.-Y. (1999). Automated surface inspection for directional textures. Image and Vision Computing, 18(1), 49-62.
 Choi, K.-J., Lee, Y.-H., Moon, J.-W., Park, C. K., Harashima, F. (2007). Development of an automatic stencil inspection system using modified Hough transform and fuzzy logic. IEEE Transactions on Industrial Electronics, 54(1), 604-611.
 Ozdemir, S., Ercil, A. (1996). Markov random fields and Karhunen-Loeve transforms for defect inspection of textile products, in Emerging Technologies and Factory Automation, 1996. EFTA ‘96. Proceedings, 1996 IEEE Conference on, 1996.
 Yu, X., Hu, J., Baciu, G. (2005). Defect detection of jacquard fabrics using multiple color-channel analysis. Research Journal of Textile and Apparel, 9(1), 21-29.
 Siegmund, D., Samartzidis, T., Fu, B., Braun, A., Kuijper, A. (2017). Fiber defect detection of inhomogeneous voluminous textiles, in Pattern Recognition, Springer International Publishing, Huatulco, Mexico, 278-287.
 Turner, M. R. (1986). Texture discrimination by Gabor functions. Biological Cybernetics, 55(2-3), 71-82.
 Clark, M., Bovik, A., Geisler, W. (1987). Texture segmentation using Gabor modulation/demodulation. Pattern Recognition Letters, 6(4), 261-267.
 Yanbei, L., Zhitao, X., Jun, W., Fang, Z. (2011). Fabric defect detection method based on optimal Gabor filter bank. International Journal of Digital Content Technology and its Applications, 5(11).