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Distance Corrections01:15

Distance Corrections

To achieve precise distance measurements, especially in surveying and construction, certain corrections must be applied to account for potential sources of error like the standardization errors, temperature variations, and slope adjustments.Standardization error emerges when measurement equipment undergoes changes, such as wear, repairs, or weather impacts. To address this, surveyors compare the equipment’s readings to a standard. This process identifies any deviation that might lead to...

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Related Experiment Video

Updated: Jun 12, 2026

Sample Drift Correction Following 4D Confocal Time-lapse Imaging
10:04

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Published on: April 12, 2014

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unDrift: A versatile software for fast offline SPM image drift correction.

Tobias Dickbreder1, Franziska Sabath1, Lukas Höltkemeier1

  • 1Physical Chemistry I, Bielefeld University, Universitätsstraße 25, 33615 Bielefeld, Germany.

Beilstein Journal of Nanotechnology
|January 3, 2024
PubMed
Summary

Thermal drift distorts scanning probe microscopy (SPM) data. We introduce unDrift, a software tool for fast, reliable SPM image drift correction, simplifying analysis of long image series.

Keywords:
atomic force microscopycalibrationdrift correctionimage correlation functionsperiodic structuresscanning probe microscopy

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Area of Science:

  • Surface science
  • Materials science
  • Nanotechnology

Background:

  • Scanning probe microscopy (SPM) is crucial for surface and interface analysis in physics and chemistry.
  • Thermal drift is a significant artifact in SPM, distorting data and complicating analysis, especially for long image series.
  • Existing offline drift correction methods are often time-consuming and tedious.

Purpose of the Study:

  • To develop and present unDrift, an easy-to-use software for rapid and accurate drift correction of SPM images.
  • To provide efficient offline drift correction solutions for SPM data analysis.
  • To enable reliable analysis of extensive SPM image datasets.

Main Methods:

  • unDrift employs three algorithms to determine drift velocity from consecutive SPM images.
  • Algorithms include semi-automatic analysis of periodic structure distortion and automatic or manual evaluation of stationary feature movement.
  • Correction can be performed without additional reference data or overlapping scan areas.

Main Results:

  • unDrift successfully corrects SPM images even with high drift velocities, partial data usability, or weak contrast.
  • The semi-automatic algorithm effectively corrects drift in long series of hundreds of images, demonstrated on calcite-water interface data.
  • The software offers versatile drift correction capabilities for various SPM data challenges.

Conclusions:

  • unDrift provides a fast, reliable, and user-friendly solution for SPM image drift correction.
  • The software enhances the efficiency of analyzing extensive SPM datasets, overcoming limitations of existing tools.
  • unDrift's algorithms are robust and applicable to challenging datasets, improving data quality and interpretability.