Journal
APPLIED SURFACE SCIENCE
Volume 375, Issue -, Pages 118-126Publisher
ELSEVIER
DOI: 10.1016/j.apsusc.2016.03.013
Keywords
Magnetic tile; Surface defect detection; The shearlet transform; Machine vision
Categories
Funding
- National Key Technology RD Program [2015BAF02B02]
- Science and Technology Support Plan Project of Sichuan province [2014GZX0001]
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In this paper, we propose a defect extraction method for magnetic tile images based on the shearlet transform. The shearlet transform is a method of multi-scale geometric analysis. Compared with similar methods, the shearlet transform offers higher directional sensitivity and this is useful to accurately extract geometric characteristics from data. In general, a magnetic tile image captured by CCD camera mainly consists of target area, background. Our strategy for extracting the surface defects of magnetic tile comprises two steps: image preprocessing and defect extraction. Both steps are critical. After preprocessing the image, we extract the target area. Due to the low contrast in the magnetic tile image, we apply the discrete shearlet transform to enhance the contrast between the defect area and the normal area. Next, we apply a threshold method to generate a binary image. To validate our algorithm, we compare our experimental results with Otsu method, the curvelet transform and the nonsubsampled contourlet transform. Results show that our algorithm outperforms the other methods considered and can very effectively extract defects. (C) 2016 Elsevier B.V. All rights reserved.
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