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Study on defect detection of IC wafer based on morphology

机译:基于形态学的IC晶圆缺陷检测研究

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With the development of the micro-processing, silicon material technique, the silicon structural design, mass production, the scientific researches on integrated circuit have been developed rapidly. Defect detection and fault diagnosis as critical design requirements is necessary to achieve high-quality, cost-effective multichip systems. An increasingly difficult task, however, is the inherent need to accurately locate, identify the defects within the microchip. A method of defect detection of IC wafer has been investigated using mathematical morphology. Firstly, the differential charts of the pending images and the intact image of IC wafer are computed and digitized to two gray levels, i.e. black and white. Secondly, the brightness of the pending images have been transformed to the same brightness as that of intact image in order to make the arithmetic is robust for various illumination conditions. Next, the defects on the binary image of differential chart can be found and dealt with mathematical morphology. Finally, several representative characteristics are proposed to extract and describe the defects of IC wafer image, for example perimeter, area, macro axis, minor axis, eccentricity ratio, centroid, circularity and rectangular degree, etc.
机译:随着微处理技术,硅材料技术,硅结构设计,批量生产以及集成电路科学研究的飞速发展。缺陷检测和故障诊断是实现高质量,高性价比的多芯片系统所必需的关键设计要求。然而,日益困难的任务是精确定位,识别微芯片内缺陷的内在需求。已经使用数学形态学研究了IC晶片的缺陷检测方法。首先,计算IC晶片的待处理图像和完整图像的差分图并将其数字化为两个灰度级,即黑色和白色。其次,将待处理图像的亮度转换为与完整图像相同的亮度,以使算法在各种照明条件下都具有鲁棒性。接下来,可以找到微分图二值图像上的缺陷,并用数学形态进行处理。最后,提出了几种具有代表性的特征来提取和描述IC晶片图像的缺陷,例如周长,面积,宏轴,短轴,偏心率,质心,圆度和矩形度等。

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