Faulty Scarfing Slab Detection Using Machine Vision

Abstract:

In this study, we developed a detection algorithm using machine vision for faulty scarfing on slabs. Scarfing is a process for burning out defective areas on the surface of semi-finished steel products so that the product is suitable for subsequent rolling or forging. In the case of rolling, a poorly scarfed slab can cause serious defects. Therefore, an automatic inspection system for scarfed slabs should be developed. In the image of faultily scarfed slab, discontinuous bright bands and borderlines are observed. To detect the bright bands, we examined the real part of a Gabor filter. However, because the size of the bright bands is not fixed, the parameters of the real part of the Gabor filter were determined adaptively using the imaginary part of the Gabor filter. The performance of the proposed algorithm was tested with 2292 images of scarfed slabs of which 49 of the images were of faulty scarfed slabs. The proposed algorithm was able to detect defects with 95.9% accurate and the false alarm was 1.6%.

• Periodical: Advanced Materials Research (Volume 462)
• Pages: 185-190
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.462.185
• Online since: February 2012
• Authors: Doo Chul Choi, Yong Ju Jeon, Sang Woo Kim
• Keywords: Defect Detection, Gabor Filter, Inspection, Machine Vision, Steel Product

References

[1] J. -H. Oh, B. –J. Yun, S. –Y. Kim, and K. –H. Park, A Development of the TFT-LCD Image Defect Inspection Method Based on Human Visual System, IEICE Tran. Fundamentals, 2008, vol. e91, 1400-1407.

DOI: 10.1093/ietfec/e91-a.6.1400

[2] A. Kumar, and G. K. H. Pang, Defect Detection in Textured Materials Using Gabor Filters, IEEE Trans. On Industry Applications, 2002, 38(2), 425-440.

DOI: 10.1109/28.993164

[3] Z. Chen, Y. Tao, and X. Chen, Multiresolution Local Contrast Enhancement of X-ray Images for Poultry Meat Inspection, Appl. Opt., 2001, 40(8), 1195-1200.

DOI: 10.1364/ao.40.001195

[4] H. Elbehiery, A. Hefnawy, and M. Elewa, Surface Defects Detection for Ceramic Tiles Using Image Processing and Morphological Techniques, 3rd World Enformatika Society Conference on Computer, Electrical, Systems Science, and Engineering, Istanbul, Turkey, 2005, 158-162.

[5] C. -S. Cho, B. -M. Chung, and R. –J. Park, Development of Real-Time Vision-Based Fabric Inspection System, IEEE Trans. Industrial Electronics, 2005, 52(4), 1073-1079.

DOI: 10.1109/tie.2005.851648

[6] J. P. Yun, S. H. Choi, B. Seo, and S. W. Kim, Real-time Vision-based Defect Inspection for High-speed Steel Products, Opt. Eng., 2008, 47(5), 077204 1-8.

DOI: 10.1117/1.2957958

[7] J. P. Yun, S. H. Choi, J. –W. Kim, and S. W. Kim, Automatic Detection of Cracks in Raw Steel Block using Gabor Filter by Univariate Dynamic Encoding Algorithm for Searches (uDEAS), 2009, NDT&E International, Vol. 42, pp.389-397. (2009).

DOI: 10.1016/j.ndteint.2009.01.007

[8] Q. Li, J. You, L. Zhang, and P. Bhattacharya, Automated Retinal Vessel Segmentation Using Gabor Filters and Scale Multiplication, 2008, Proc. International Conference on Image Processing, Computer Vision, and Pattern Recognition, Las Vegas, USA, 22-28.

DOI: 10.1109/icsmc.2006.384665

[9] D. Casasent, J. S. Smokelin, Real, Imaginary, and Clutter Gabor Filter Fusion for Detection with Reduced False Alarms, 1994, Opt Eng., 33(7): 2255–63.

DOI: 10.1117/12.172407