# Automatic drift compensation for nanoscale imaging using feature point matching

https://mdr.nims.go.jp/datasets/15adbe74-0767-42f4-970c-8a741fa4018f

## File

- [article.pdf](https://mdr.nims.go.jp/filesets/0ccbab6e-02bc-4939-8142-12f5c82ee543/download) ([Detail](https://mdr.nims.go.jp/filesets/0ccbab6e-02bc-4939-8142-12f5c82ee543.md))

## Id

15adbe74-0767-42f4-970c-8a741fa4018f

## Local identifier



## Visibility

open_to_public

## State

published

## Created at

2024-12-10T04:02:03.100374Z

## Updated at

2024-12-10T07:56:37.468609Z

## Published at

2024-12-10T07:56:37.532566Z

## Doi

https://doi.org/10.48505/nims.5133

## First published url

https://doi.org/10.1063/5.0139330

## Date published

2023-03-20

## Recorded date published

2023-3-20

## Resource type

journal_article

## Manuscript type

accepted_manuscript

## Collection



## Title

- title: Automatic drift compensation for nanoscale imaging using feature point matching
  title_type: original
  lang: en

## Description

- description: 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.
  description_type: abstract
  lang: und

## Creator

- name: Zhuo Diao
  role: author
- name: Keiichi Ueda
  role: author
- name: Linfeng Hou
  role: author
- name: Hayato Yamashita
  role: author
- name: Oscar Custance
  role: author
  orcid: https://orcid.org/0000-0001-7931-603X
  organization: National Institute for Materials Science
- name: Masayuki Abe
  role: author

## Contact agent



## Publisher

organization: AIP Publishing

## Managing organization



## Keyword

- subject: canning probe microscopy
  schema: not_defined
- subject: computer vision
  schema: not_defined
- subject: automatic drift compensation
  schema: not_defined
- subject: atomic resolution
  schema: not_defined

## Rights

- description: '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.'
  identifier: http://rightsstatements.org/vocab/InC/1.0/

## Other identifier(s)



## Data origin

- data_origin_type: other

## Embargo



## Journal

- title: Applied Physics Letters
  issn: '00036951'
  volume: '122'
  issue: '12'
  article_number: '121601'

## Conference



## Related item



## Funding

- identifier: 19H05789
  funder_name: Japan Society for the Promotion of Science
- identifier: 21H01812
  funder_name: Japan Society for the Promotion of Science London
- identifier: 21K18876
  funder_name: Japan Society for the Promotion of Science London
- identifier: PF2010
  funder_name: National Institute for Materials Science
- identifier: PF3130
  funder_name: National Institute for Materials Science
- identifier: QN3510
  funder_name: National Institute for Materials Science
- identifier: JPMJSP2138
  funder_name: JST SPRING

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## Fileset

- id: 0ccbab6e-02bc-4939-8142-12f5c82ee543
  filename: article.pdf
  content_type: application/pdf
  size: 1362265
  md5: b05040190ed2cd6f0c22b6046ad51064

## Thumbnail

fileset_id: 0ccbab6e-02bc-4939-8142-12f5c82ee543
filename: article.pdf