【摘要】 提出了一种基于图像配准的超扭曲向列液晶显示器件(STN-LCD)的外观缺陷自动检测方法。该方法首先对标准模板图像做不均匀光照消除、二值化以及区域信息提取;然后通过控制点检测和仿射变换实现待检测图像和模板图像之间的配准;并利用各图形区域的灰度平均值和标准方差等统计信息,检测缺段、针孔等各类缺陷。为提高图像配准精度,进一步提出了有效控制点筛选方案以及混合插值方法。实验结果表明,该方法设计思路合理,缺陷检测正确率达到98.3%,可代替人眼实现对STN-LCD多种外观缺陷的快速、自动检测,满足实际应用需求。更多还原

【Abstract】 a method based on the technique of image registration is proposed for detecting the appearance defects of Super-twisted Nematic Liquid Crystal Display (STN-LCD). The standard template LCD image is first recovered from possible non-uniform illumination, and then the statistical information of each region is collected by image thresholding and region labeling. The template and testing image are registered by control-point detection and affine transform. The defects including stroke-loss and pinhole of the LCD can then be detected by using region statistics such as mean and standard deviation of grayscales. To improve the accuracy of image registration, a special scheme of control-point selection and hybrid image interpolation is proposed. Experimental results show that the proposed method is robust and accurate, and can detect STN-LCD defects automatically. The proposed method is used for industrial applications, and offers advantages over the traditional manual inspection manner.更多还原