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Precise 3-D microscopic profilometry using diffractive image microscopy and artificial neural network in single-exposure manner
Optics and Lasers in Engineering ( IF 3.5 ) Pub Date : 2021-07-06 , DOI: 10.1016/j.optlaseng.2021.106732
Guo-Wei Wu, Liang-Chia Chen

A single-exposure microscopic profilometry using artificial neural network (ANN) was developed for 3-D profile reconstruction of precise surface geometry. Optical profilometry is an important technique widely applied in many fields. However, in addition to optical aberration of the microscope itself, tilting of a local testing surface can affect the direction of the reflected light, thus causing undesired measurement errors. To overcome these problems, various methods or optical strategies have been developed, but most of them suffer from undue measurement errors attributed to the local surface gradient formed by the measured point and its neighboring surface geometry. This study proposed a novel method that combined diffractive image microscopy (DIM) with ANN. To train the ANN model, diffractive images of various surface orientations were collected for learning the complex mapping relationships between diffractive images and their corresponding surface orientations. The proposed method could simultaneously measure the height, tilting angle and tilting direction of a local surface. 3-D surface reconstruction by the proposed method required no prior knowledge of neighboring geometric information adjacent to the measured point. Using the developed approach achieved a surface height repeatability of 0.257 μm and a surface inclined angle repeatability of 0.037°, evidencing the realization of precise 3-D microscopic profilometry.



中文翻译:

使用衍射图像显微镜和人工神经网络以单次曝光方式进行精确的 3-D 显微轮廓测量

开发了使用人工神经网络 (ANN) 的单次曝光显微轮廓测量法,用于精确表面几何形状的 3-D 轮廓重建。光学轮廓测量法是一项广泛应用于许多领域的重要技术。然而,除了显微镜本身的光学像差之外,局部测试表面的倾斜会影响反射光的方向,从而导致不希望的测量误差。为了克服这些问题,已经开发了各种方法或光学策略,但大多数方法或光学策略都存在不适当的测量误差,这归因于由测量点及其相邻表面几何形状形成的局部表面梯度。本研究提出了一种将衍射图像显微镜 (DIM) 与 ANN 相结合的新方法。为了训练 ANN 模型,收集各种表面方向的衍射图像,以学习衍射图像与其对应表面方向之间的复杂映射关系。该方法可以同时测量局部表面的高度、倾斜角度和倾斜方向。通过所提出的方法进行的 3-D 表面重建不需要与测量点相邻的相邻几何信息的先验知识。使用开发的方法实现了 0.257 μm 的表面高度重复性和 0.037° 的表面倾斜角重复性,证明实现了精确的 3-D 显微轮廓测量。局部曲面的倾斜角度和倾斜方向。通过所提出的方法进行的 3-D 表面重建不需要与测量点相邻的相邻几何信息的先验知识。使用开发的方法实现了 0.257 μm 的表面高度重复性和 0.037° 的表面倾斜角重复性,证明实现了精确的 3-D 显微轮廓测量。局部曲面的倾斜角度和倾斜方向。通过所提出的方法进行的 3-D 表面重建不需要与测量点相邻的相邻几何信息的先验知识。使用开发的方法实现了 0.257 μm 的表面高度重复性和 0.037° 的表面倾斜角重复性,证明实现了精确的 3-D 显微轮廓测量。

更新日期:2021-07-07
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