Defect inspection of patterned thin film transistor-liquid crystal display panels using a fast sub-image-based singular value decomposition
Defect inspection of patterned thin film transistor-liquid crystal display panels using a fast sub-image-based singular value decomposition
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DOI：
10.1080/00207540410001716480
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发表时间：
2004-10
影响因子：
9.2
通讯作者：
C.-J. Lu;D.-M. Tsai *
中科院分区：
文献类型：
--
作者：
C.-J. Lu;D.-M. Tsai *
薄膜晶体管-液晶显示器（tft - lcd）作为一种显示器件越来越受到人们的欢迎和欢迎。提出了一种用于图像化TFT-LCD表面微缺陷自动检测的机器视觉方法。该方法基于奇异值分解的全局图像重构方案。为了减少奇异值分解的计算时间，采用了将输入图像分割成不重叠的子图像的分割方法。将像素图像作为矩阵，分解对角矩阵上的奇异值表示TFT-LCD图像的不同结构细节。该方法首先选取代表TFT-LCD表面重复正交线纹理的优势奇异值；然后通过排除占主导地位的奇异值重构矩阵。所得到的图像能够有效地去除背景纹理并清晰地保留异常。实验评估了不同图像分辨率下的TFT-LCD微缺陷，包括针孔、划痕、颗粒和指纹。实验结果表明，该方法对TFT-LCD面板的微缺陷检测是有效的。
Thin film transistor-liquid crystal displays (TFT-LCDs) have become increasingly attractive and popular as display devices. A machine vision approach is proposed for automatic inspection of microdefects in patterned TFT-LCD surfaces. The proposed method is based on a global image reconstruction scheme using singular value decomposition. A partition procedure that separates the input image into non-overlapping sub-images is used to reduce the computation time of singular value decomposition. Taking the pixel image as a matrix, the singular values on the decomposed diagonal matrix represent different structural details of the TFT-LCD image. The proposed method first selects the dominant singular values that represent the repetitive orthogonal-line texture of the TFT-LCD surface. It then reconstructs the matrix by excluding the dominant singular values. The resulting image can effectively remove the background texture and preserves anomalies distinctly. The experiments have evaluated a variety of TFT-LCD microdefects including pinholes, scratches, particles and fingerprints at different image resolutions. The experimental results reveal that the proposed method is effective and efficient for microdefect inspection of TFT-LCD panels.