time delay and integration
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Micromachines ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 135
Author(s):  
Fu-Ming Tzu

The paper presents a typology of electrical open and short defects on thin-film transistors (TFT) using an electrical tester and automatic optical inspection (AOI). The experiment takes the glass 8.5th generation to detect the electrical characteristics engaged with time delay and integration (TDI) charged-coupled-devices (CCDs), a fast line-scan, and a review CCD with five sets of magnification lenses for further inspection. An automatic data acquisition program (ADAP) controls the open/short (O/S) sensor, TDI-CCD, and motor device for machine vision and statistics of substrate defects simultaneously. Furthermore, the quartz mask installed on AOI verified its optical resolution; a TDI-CCD can grab an image of a moving object during transfers of the charge in synchronous scanning with the object that is significant.


2019 ◽  
Vol 39 (9) ◽  
pp. 0911001
Author(s):  
陶淑苹 Shuping Tao ◽  
张续严 Xuyan Zhang ◽  
冯钦评 Qinping Feng ◽  
宋明珠 Mingzhu Song ◽  
吴勇 Yong Wu

2012 ◽  
Vol 10 ◽  
pp. 145-151 ◽  
Author(s):  
J. Dörr ◽  
M. Rosenbaum ◽  
W. Sauer-Greff ◽  
R. Urbansky

Abstract. In food industry, most products are checked by X-rays for contaminations. These X-ray machines continuously scan the product passing through. To minimize the required X-ray power, a Time, Delay and Integration (TDI) CCD-sensor is used to capture the image. While the product moves across the sensor area, the X-ray angle changes during the pass. As a countermeasure, adjusting the sensor shift speed on a single focal plane of the product can be selected. However, the changing angle result in a blurred image in dependance to the thickness of the product. This so-called ''laminographic effect'' can be compensated individually for one plane by inverse filtering. As the plane of contamination is unknown, the blurred image will be inversely filtered for different planes, but only one of these images shows the correctly focussed object. If the correct image can be found, the plane containing the contamination is identified. In this contribution we demonstrate how the correctly focussed images can be found by analyzing the images of all planes. Different characteristics for correctly and incorrectly focussed planes like sharpness, number of objects and edges are investigated by using image processing algorithms.


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