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Pinhole detection in steel slab images using Gabor filter and morphological features

机译:使用Gabor滤波器和形态特征检测钢板图像中的针孔

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摘要

Presently, product inspection for quality control is becoming an important part in the steel manufacturing industry. In this paper, we propose a vision-based method for detection of pinholes in the surface of scarfed slabs. The pinhole is a very tiny defect that is 1-5 mm in diameter. Because the brightness in the surface of a scarfed slab is not uniform and the size of a pinhole is small, it is difficult to detect pinholes. To overcome the above-mentioned difficulties, we propose a new defect detection algorithm using a Gabor filter and morphological features. The Gabor filter was used to extract defective candidates. The morphological features are used to identify the pinholes among the defective candidates. Finally, the experimental results show that the proposed algorithm is effective to detect pinholes in the surface of the scarfed slab.
机译:当前,用于质量控制的产品检验正成为钢铁制造业的重要组成部分。在本文中,我们提出了一种基于视觉的方法来检测斜切板表面的针孔。针孔是直径1-5毫米的非常微小的缺陷。由于斜切板表面的亮度不均匀且针孔的尺寸小,因此难以检测针孔。为了克服上述困难,我们提出了一种新的利用Gabor滤波器和形态学特征的缺陷检测算法。 Gabor滤波器用于提取有缺陷的候选对象。形态特征用于识别有缺陷的候选材料之间的针孔。最后,实验结果表明,该算法能够有效检测斜切板表面的针孔。

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