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Detection of Local Mura Defects in TFT-LCD Using Machine Vision

机译:使用机器视觉检测TFT-LCD中的局部Mura缺陷

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Machine vision is widely used in the field of defect inspection. Mura is a typical defect of LCD panel, appearing as local lightness variation with low contrast and blurry contour, so it is hard to be inspected with traditional thresholding or edge detection methods. This paper presents a machine vision Mura inspection method based on real Gabor filter. By selecting appropriate number of filtering scale and orientation, a set of real Gabor filter are formed and applied to the LCD images with defects. Then, through images fusion, all the sub-images from different channels are fused together and as a result, the global structurally textured backgrounds are eliminated and the local defects are preserved. As expected, the final binary images show the defects out. Experiments show that this method is suitable to the inspection of many types of Mura. Furthermore, it is insensitive to the rotation of image.
机译:机器视觉广泛用于缺陷检查领域。 Mura是LCD面板的典型缺陷,表现为局部亮度变化,对比度低且轮廓模糊,因此很难通过传统的阈值或边缘检测方法进行检查。本文提出了一种基于真实Gabor滤波器的机器视觉Mura检测方法。通过选择适当数量的滤波比例和方向,可以形成一组真实的Gabor滤波器,并将其应用于有缺陷的LCD图像。然后,通过图像融合,将来自不同通道的所有子图像融合在一起,结果,消除了整体结构纹理背景,并保留了局部缺陷。不出所料,最终的二进制图像显示出了缺陷。实验表明,该方法适用于多种类型的Mura的检查。此外,它对图像的旋转不敏感。

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