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Scanning Electron Microscope Calibration Using a Multi-Image Non-Linear Minimization Process
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DOI：10.1080/15599612.2015.1034903.png)
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Abstract
En 中文
A scanning electron microscope (SEM) calibrating approach based on non-linear minimization procedure is presented in this article1 (1)A part of this article has been published in IEEE International Conference on Robotics and Automation (ICRA), 2014. . Both the intrinsic parameters and the extrinsic parameters estimations are achieved simultaneously by minimizing the registration error. The proposed approach considers multi-images of a multi-scale calibration pattern view from different positions and orientations. Since the projection geometry of the scanning electron microscope is different from that of a classical optical sensor, the perspective projection model and the parallel projection model are considered and compared with distortion models. Experiments are realized by varying the position and the orientation of a multi-scale chessboard calibration pattern from 300x to 10,000x. The experimental results show the efficiency and the accuracy of this approach.
Keywords:
Sensor calibration
Micro/nano robotics
Machine vision on micro/nano scale
Scanning Electron Microscope
Camera projection model
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