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Related Concept Videos

Instrument Calibration01:12

Instrument Calibration

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Instrument calibration is essential for ensuring that instruments produce accurate and consistent results. It is vital in manufacturing, healthcare, testing laboratories, and scientific research. Calibration processes are specific to each instrument and help enhance data accuracy. Each instrument has a unique calibration process tailored to its design and function to improve data accuracy.
Analytical Balance Calibration
An analytical balance measures mass and requires regular calibration to...
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Calibration Curves: Linear Least Squares01:20

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A calibration curve is a plot of the instrument's response against a series of known concentrations of a substance. This curve is used to set the instrument response levels, using the substance and its concentrations as standards. Alternatively, or additionally, an equation is fitted to the calibration curve plot and subsequently used to calculate the unknown concentrations of other samples reliably.
For data that follow a straight line, the standard method for fitting is the linear...
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Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters
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Calibration of a Hyper-Spectral Imaging System Using a Low-Cost Reference.

Muhammad Saad Shaikh1, Keyvan Jaferzadeh1,2, Benny Thörnberg1

  • 1Department of Electronics Design, Mid Sweden University, 851 70 Sundsvall, Sweden.

Sensors (Basel, Switzerland)
|June 2, 2021
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Summary

This study introduces a new hyper-spectral imaging system with a low-cost calibration method. The system accurately measures material reflectance, proving effective for classifying winter road conditions like snow and ice.

Keywords:
InGaAsPTFEcalibrationdark currenthyperspectral imagingpush-broom cameraspectralonteflonwinter road conditions

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Area of Science:

  • Optics and Photonics
  • Remote Sensing
  • Materials Science

Background:

  • Accurate material characterization is crucial for various applications.
  • Existing hyperspectral imaging calibration methods can be complex and costly.
  • Developing robust and cost-effective calibration techniques is essential for wider adoption.

Purpose of the Study:

  • To present a novel hyper-spectral imaging system.
  • To introduce a practical and low-cost calibration procedure for the system.
  • To demonstrate the system's capability in classifying winter road conditions.

Main Methods:

  • Utilized a hyperspectral camera with an active illumination source featuring variable spectral intensity.
  • Employed a low-cost polytetrafluoroethylene (PTFE) calibration reference for relative reflectance measurements.
  • Acquired spectral images of various road surfaces (snow, icy asphalt, dry asphalt, wet asphalt) under diverse illumination spectra and exposure times.
  • Applied Principal Component Analysis (PCA) for spectral data analysis.

Main Results:

  • Demonstrated that relative reflectance measurements are independent of illumination spectral distribution and camera sensitivity.
  • Achieved well-separated data clusters for different road conditions using PCA.
  • Confirmed the system's suitability for material classification based on spectral data.

Conclusions:

  • The developed hyper-spectral imaging system and calibration procedure are effective and practical.
  • The system provides reliable material reflectance measurements, independent of lighting conditions.
  • The system shows significant potential for accurate classification of road surface conditions in winter environments.