图像拼接
计算机视觉
像素
人工智能
亮度
计算机科学
亮度
边缘检测
失真(音乐)
光学
GSM演进的增强数据速率
校准
计算机图形学(图像)
图像处理
图像(数学)
物理
放大器
计算机网络
带宽(计算)
量子力学
作者
Yao Zhang,Jianxu Mao,Yaonan Wang,Caiping Liu,Hui Zhang,Haoran Tan,Kai Zeng
出处
期刊:IEEE Transactions on Instrumentation and Measurement
[Institute of Electrical and Electronics Engineers]
日期:2022-01-01
卷期号:71: 1-12
被引量:1
标识
DOI:10.1109/tim.2022.3206836
摘要
Vision-based inspection, measurement, and repair technologies are becoming extremely significant in the manufacturing of display screens. These allow for concurrent luminance measurement and defect detection across millions of display sub-pixels. However, for curved OLED displays, the image quality of curved edges is too poor and the localization of sub-pixel-level pixel or defects cannot be achieved. As a result, detection and measurement algorithms or systems that would otherwise work on flat screens fail when rolled out to curved screens. In this paper, we proposed a Stitching-Based-on-Corrections (SBoC) method to obtain a standardized flat image on OLED displays with curved edges. This allows traditional methods to become applicable again. First, reflective prisms were added to the imaging system to capture clear images of the curved-edge regions of the display screen. Then, an active calibration image flattening algorithm based on polynomial geometric correction was proposed to standardize the images on the display screen. Second, we designed adaptive gray-level corrections perpendicular and parallel to the principal axis of the reflective prisms to restore the brightness and contrast of curved-edge regions to an ideal flat state. The corrected images of different regions were then stitched together, and an ideal, distortion-free image was produced, with pixels distributed in a strict regular pattern. The experimental results confirmed the effectiveness of the proposed method.
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