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Three-dimensional Structure Recognition of Circuit Patterns on Semiconductor Devices Using Multiple SEM Images Detected in Different Electron Scattering Angles

机译:使用在不同电子散射角下检测到的多个SEM图像识别半导体器件上电路图案的三维结构

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We propose a method for recognizing the three-dimensional structure of circuit patterns to achieve automatic pattern width measurement of semiconductor devices using scanning electron microscope (SEM). Pattern measurement requires pattern recognition technique to identify the measurement position from an SEM image. However, pattern width and brightness values on an image fluctuate according to patterning conditions, type of material, etc., so distinguishing between line and space through image matching based on brightness information is difficult. In view of this problem, we investigated a line and space discrimination method that focuses on fundamentally different three-dimensional structures (concavity and convexity) and considering that this difference between concavity and convexity appears as a difference in the scattering angles of secondary electrons, we captured two images corresponding to these two scattering angles. In this way, we were able to design image feature that portray the difference between line and space from these two images and perform high-speed and easy capture of concavity and convexity information. In experiments, the proposed method achieved a 100% accuracy rate in automatic critical-dimension measurements.
机译:我们提出一种识别电路图案的三维结构的方法,以实现使用扫描电子显微镜(SEM)的半导体器件的自动图案宽度测量。模式测量需要模式识别技术,才能从SEM图像中识别测量位置。然而,图像上的图案宽度和亮度值根据图案形成条件,材料的类型等而波动,因此难以通过基于亮度信息的图像匹配来区分线和空间。针对这个问题,我们研究了一种线和空间判别方法,该方法着眼于根本不同的三维结构(凹面和凸面),并考虑到凹面和凸面之间的这种差异表现为二次电子的散射角的差异,我们捕获了与这两个散射角相对应的两个图像。这样,我们就能够设计出能够从这两个图像描绘出线条和空间之间差异的图像特征,并能够快速,轻松地捕获凹凸信息。在实验中,所提出的方法在自动关键尺寸测量中达到了100%的准确率。

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