Abstract
Observing the sample under a scanning electron microscope (SEM) requires adjustment of brightness and contrast to obtain a clear image. The traditional method is manually adjusted by the operator, which inevitably has errors. In this paper, an adaptive threshold processing method based on image-based normalized gray histogram is proposed. This method can acquire the threshold of the image according to the state of the currently obtained secondary electron images. When the brightness and contrast of the image change, the threshold can also be changed accordingly. It is concluded from a large number of tests that when the secondary electron image gray histogram has obvious double peaks and is located in the trough, the threshold obtained is optimal. Therefore, it is possible to better observe the pictures under the SEM.
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Acknowledgments
This work is supported by National Key R&D Program of China (2018YFB1304901).
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Bian, W., Wang, M., Yang, Z. (2019). Adaptive Threshold Processing of Secondary Electron Images in Scanning Electron Microscope. In: Yu, H., Liu, J., Liu, L., Ju, Z., Liu, Y., Zhou, D. (eds) Intelligent Robotics and Applications. ICIRA 2019. Lecture Notes in Computer Science(), vol 11740. Springer, Cham. https://doi.org/10.1007/978-3-030-27526-6_15
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DOI: https://doi.org/10.1007/978-3-030-27526-6_15
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