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A novel surface defect inspection algorithm for magnetic tile

机译:一种新型的磁砖表面缺陷检测算法

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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.
机译:本文提出了一种基于剪切波变换的磁砖图像缺陷提取方法。剪切波变换是一种多尺度几何分析方法。与类似方法相比,小波变换具有更高的方向灵敏度,这对于从数据中准确提取几何特征很有用。通常,CCD摄像机捕获的磁砖图像主要由目标区域,背景组成。我们提取磁砖表面缺陷的策略包括两个步骤:图像预处理和缺陷提取。这两个步骤都很关键。在对图像进行预处理之后,我们提取目标区域。由于磁砖图像中的对比度较低,因此我们应用离散小波变换来增强缺陷区域和正常区域之间的对比度。接下来,我们应用阈值方法生成二进制图像。为了验证我们的算法,我们将我们的实验结果与Otsu方法,curvelet变换和非下采样Contourlet变换进行了比较。结果表明,我们的算法优于其他方法,可以非常有效地提取缺陷。 (C)2016 Elsevier B.V.保留所有权利。

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