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Detection of Water-Stains Defects in TFT-LCD Based on Machine Vision

机译:基于机器视觉的TFT-LCD水渍缺陷检测

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TFT-LCD is an important part of the mobile phone, and the defect detection of it requires a lot of manpower and material resources. Common TFT -LCD defects include point defect, line defect and Mura defect. The water-stains defects are a common Mura defect. This paper presents an efficient algorithm for detecting water defects. The first step is to strengthen the detect features by band-pass filter. Then, Sobel edge detection operator is used to enhance the edge of the abnormal defect. The backlight of the mobile phone screen may not be uniformly distributed, and the enhanced image takes on an irregular texture background, so the screen can be divided into several small blocks. After that, a background assessment is made on each small piece to roughly locate where the defect area is. Finally, to make a second judge on the small pieces of interest, a SVM classifier is trained. Through many tests in the mobile screen production workshop, the accuracy of the algorithm is 95.9%, meeting the requirements of industrial inspection.
机译:TFT-LCD是手机的重要组成部分,其缺陷检测需要大量的人力和物力。常见的TFT -LCD缺陷包括点缺陷,线缺陷和Mura缺陷。水渍缺陷是常见的Mura缺陷。本文提出了一种有效的水缺陷检测算法。第一步是通过带通滤波器来增强检测功能。然后,使用Sobel边缘检测算子来增强异常缺陷的边缘。手机屏幕的背光可能分布不均匀,并且增强后的图像具有不规则的纹理背景,因此可以将屏幕分为几个小块。之后,对每个小块进行背景评估,以大致定位缺陷区域的位置。最后,为了对感兴趣的小片段做出第二个判断,对SVM分类器进行了训练。通过在移动屏生产车间的多次测试,该算法的准确度达到95.9 \%,满足了工业检测的要求。

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