An Algorithm for Detecting Seam Cracks in Steel Plates

In this study, we developed an algorithm for detecting seam cracks in a steel plate. Seam cracks are generated in the edge region of a steel plate. We used the Gabor filter and an adaptive double threshold method to detect them. To reduce the number of pseudo defects, features based on the shape of seam cracks were used. To evaluate the performance of the proposed algorithm, we tested 989 images with seam cracks and 9470 defect-free images. Experimental results show that the proposed algorithm is suitable for detecting seam cracks. However, it should be improved to increase the true positive rate. Keywords—Defect detection, Gabor filter, machine vision, surface inspection.

[1]  Lei Zhang,et al.  Automated Retinal Vessel Segmentation Using Gabor Filters and Scale Multiplication , 2006, IPCV.

[2]  G. G. Stokes "J." , 1890, The New Yale Book of Quotations.

[3]  SungHoo Choi,et al.  Real-time vision-based defect inspection for high-speed steel products , 2008 .

[4]  Ajay Kumar,et al.  Defect detection in textured materials using Gabor filters , 2000, Conference Record of the 2000 IEEE Industry Applications Conference. Thirty-Fifth IAS Annual Meeting and World Conference on Industrial Applications of Electrical Energy (Cat. No.00CH37129).

[5]  Sangchul Won,et al.  Vision-based inspection for periodic defects in steel wire rod production , 2010 .

[6]  Sang Woo Kim,et al.  Pinhole detection in steel slab images using Gabor filter and morphological features. , 2011, Applied optics.

[7]  David Casasent,et al.  Real, imaginary, and clutter Gabor filter fusion for detection with reduced false alarms , 1994 .