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Focus and edge detection algorithms and their relevance to the development of an optical overlay calibration standard

机译:焦点和边缘检测算法及其与光学叠加校准标准开发的相关性

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We present results of investigations into optical focus and edge detection algorithms relevant to overlay metrology. We compare gradient energy, standard deviation, contrast and summed intensity of acquired images as focus metrics for bright-field, scanning confocal, and confocal microscopy. For our purposes, gradient energy calculated via Sobel filtering was found to be the best criterion for an autofocus algorithm. We predict, based on theoretical results, that all of the focus algorithm we considered will focus in different heights relative to the object depending on the material properties of the object. Edge detection is accomplished via a window and spline technique for whole image data, and by application of a multiple line regression algorithm for single scan data. Measurements accomplished through these techniques are compared to state of the art scattering and analysis models.
机译:我们将调查结果呈现为与覆盖计量相关的光学焦点和边缘检测算法。我们将所获取图像的梯度能量,标准偏差,对比度和总和强度进行比较,作为亮场,扫描共聚焦和共聚焦显微镜的焦距。出于我们的目的,发现通过Sobel滤波计算的梯度能量是自动对焦算法的最佳标准。我们基于理论结果预测,我们所考虑的所有焦点算法将根据物体的材料属性相对于对象聚焦在不同的高度中。边缘检测是通过用于整个图像数据的窗口和样条曲线技术完成的,并且通过应用用于单扫描数据的多线回归算法。将通过这些技术完成的测量与现有技术的散射和分析模型进行比较。

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