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Automatic drift compensation for nanoscale imaging using feature point matching
An implementation of drift compensation for imaging at the nanoscale is presented. The method is based on computer vision techniques and hence applicable to any microscope that generates images through a computer interface. The algorithm extracts and matches pairs of feature points from consecutive images to compute and compensate for probe–sample misalignments over time. The protocol also applies selection rules that enable it to withstand significant changes in image contrast. We demonstrate our fully automatic implementation by continuously imaging the same area of a Si(100) surface at the atomic scale with scanning probe microscopy over a period of 25 h at room temperature, showing that the method is robust even under the presence of non-linear drift or spontaneous changes of the probe apex. We apply our method to study the movement of pairs of tin atoms confined within a half-unit cell of the Si(111)-(7 x 7) surface and estimate the energy barrier for their diffusion at room temperature.
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- 20/03/2023
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- This article may be downloaded for personal use only. Any other use requires prior permission of the author and AIP Publishing. This article appeared in Zhuo Diao, Keiichi Ueda, Linfeng Hou, Hayato Yamashita, Oscar Custance, Masayuki Abe; Automatic drift compensation for nanoscale imaging using feature point matching. Appl. Phys. Lett. 20 March 2023; 122 (12): 121601 and may be found at https://doi.org/10.1063/5.0139330.
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