Abstract
Defect detection is a key problem in quality control for many industrial fields like wallpaper scanning, ceramic flow detection and fabric inspection. For a long time the fabric defects inspection process is still carried out with human visual inspection, and thus, insufficient and costly. Therefore, automatic fabric defect inspection is required to reduce the cost and time waste caused by defects. Many techniques have been developed for detection of defects for fabrics through the years using neural networks, Fourier transform. However, most of the methods mentioned above are mainly designed for un-patterned fabric inspection. In this paper, the work is concentrated on the patterned texture inspection of the fabrics, using regular bands and enhancement of these images using linear quadratic programming.
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References
Amet, A.L., Ertuzun, A., Ercil, A.: An efficient method for texture defect detection: Sub-band domain co-occurrence matrices. Image Vis. Comput. 18, 543–553 (2000)
Wang, C., Ye, Z.: Brightness preserving histogram equalization with maximum entropy: A variational perspective. IEEE Trans. on Consumer Electronics 51(4), 1326–1334 (2005)
Escofet, J., Navarro, R., Millán, M.S., Pladellorens, J.: Detection of local defects in textile webs using Gabor filters. In: Refregier, P. (ed.) Vision Systems: New Image Processing Techniques. Proceedings SPIE, vol. 2785, pp. 163–170 (1996)
Escofet, J., Navarro, R., Millan, M.S., Pladellorens, J.: Detection of local defects in textile webs using Gabor filters. Opt. Eng. 37(8), 2297–2307 (1998)
Hu, M.C., Tsai, I.S.: Fabric Inspection Based on best Wavelet Packet Bases. Textile Res. J. 70(8), 662–670 (2000)
Ngan, H.Y.T., Pang, G.K.H.: Novel method for patterned fabric inspection using Bollinger bands. Optical Engineering, Society of Photo-Optical Engineers (August 2006)
Ngan, H.Y.T., Pang, G.K.H.: Regularity Analysis for Patterned Texture Inspection. IEEE 6(1), 131–144 (2009)
Ngan, H.Y.T., Pang, G.K.H., Yung, S.P., Ng, M.K.: Wavelet based methods on patterned fabric defect detection. Pattern Recognit. 38(4), 559–576 (2005)
Jasper, W.J., Garnier, S.J., Potlapalli, H.: Texture characterization and defect detection using adaptive wavelets. Opt. Eng. 35(11), 3140–3149 (1996)
Kang, T.J., et al.: Automatic recognition of Fabric Weave Patterns by Digital Image Analysis. Textile Res. J. 69(2), 77–83 (1999)
Kang, T.J., et al.: Automatic Structure Analysis and Objective Evaluation of Woven Fabric Using Image Analysis. Textile Res. J. 71(3), 261–270 (2001)
Chin, R.T., Harlow, C.A.: Automated visual inspection: A survey. IEEE Trans. Pattern Anal. Machine Intell. PAMI-4(6), 557–573 (1982)
Tsai, I.S., Hu, M.C.: Automatic Inspection of Fabric Defects Using an Artificial Neural Network Technique. Textile Res. J. 66(7), 474–482 (1996)
Jen, T.-C., Wang, S.-J.: Image Enhancement Based on Quadratic Programming. In: 15th IEEE Conference on ICIP 2008, pp. 3164–3167 (2008)
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Obula Konda Reddy, R., Eswara Reddy, B., Keshava Reddy, E. (2013). Texture Analysis and Defect Classification for Fabric Images Using Regular Bands and Quadratic Programming. In: Kumar M., A., R., S., Kumar, T. (eds) Proceedings of International Conference on Advances in Computing. Advances in Intelligent Systems and Computing, vol 174. Springer, New Delhi. https://doi.org/10.1007/978-81-322-0740-5_112
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DOI: https://doi.org/10.1007/978-81-322-0740-5_112
Publisher Name: Springer, New Delhi
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