基于象限梯度算子的超大尺寸液晶图像亚像素缺陷检测

Jide Qian, Wenjun Li, Bin Chen, Jiye Qian, Fengwei Liu, Xin Zhou
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引用次数: 3

摘要

针对超大尺寸液晶显示器的缺陷定位问题,提出了一种亚像素分量缺陷自动检测算法。为保证检测精度,一般采用线扫描相机对2亿像素以上的LCD进行图像采集。因此,LCD的一个微小的亚像素组件被映射成图像中的许多像素。提出了在不同象限上动态调整梯度方向的象限梯度算子。该方法可以直接检测亚像素分量缺陷,无需额外的边缘处理。为了有效、自动地检测缺陷,使用小随机采样子图像估计相关参数。投影方法估计亚像素分量之间的空间,以此估计样本大小和缺陷面积阈值。理论分析和实验结果表明,该算法能够在线性复杂度为0 ($n$)的情况下准确检测出亚像素分量缺陷。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sub-Pixel Defect Detection for Super Large LCD Images Using Quadrant Gradient Operator
This paper proposes an automatic sub-pixel component defect detection algorithm to locate the flaws of liquid crystal display (LCD) using super large images. To ensure detection accuracy, a line scan camera is used to capture the images of an LCD with more than 200 million pixels. Therefore, a tiny sub-pixel component of an LCD is mapped into many pixels in an image. The quadrant gradient operator is proposed to adjust gradient direction dynamically in different quadrants. Our method can directly detect sub-pixel component defects without extra operation to deal with edges. To detect defects efficiently and automatically, related parameters are estimated using a small random sampled sub-image. The projection method estimates the spaces between sub-pixel components, based on which the sample size and the defect area threshold can be estimated. Theoretical analysis and experimental results show that the proposed algorithm can accurately detect sub-pixel component defects in linear complexity O($n$).
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