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Study on clear stereo image pair acquisition method for small objects with big vertical size in SLM vision system.

Yuezong Wang1, Yan Jin1, Lika Wang1

  • 1College of Mechanical Engineering and Applied Electronics Technology, Beijing University of Technology, Beijing, 100124, China.

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Summary

This study introduces a microscopic image fusion method for stereo light microscopes (SLM) to create clear images of objects with large vertical sizes. The technique improves surface profile measurement by effectively combining image sequences.

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image fusionmicroscopic measurementmicroscopic visionstereo light microscope

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Area of Science:

  • Microscopy and Imaging Technology
  • Optical Engineering
  • Image Processing

Background:

  • Stereo light microscopes (SLM) are used for surface profile measurement.
  • Objects with large vertical sizes can cause clear and fuzzy regions in SLM images due to depth range limitations.
  • Existing methods struggle to produce clear fused images for such scenarios.

Purpose of the Study:

  • To develop a microscopic sequence image fusion method for SLM systems.
  • To address image fuzziness caused by the large vertical size of small objects.
  • To improve the clarity and performance of fused stereo images for surface profile measurement.

Main Methods:

  • A method for capturing and aligning image sequences was developed to produce aligned stereo images.
  • Stereo image sequences were decomposed using wavelet analysis into high and low-frequency coefficients.
  • Fused stereo images were generated using novel high and low-frequency coefficient fusion rules.

Main Results:

  • A linear relationship was identified between Δw1 (Δw2) and ΔZ in stereo image sequences, highlighting the necessity of image alignment.
  • The proposed fusion method produced clear fused stereo images.
  • The method demonstrated superior performance compared to other image fusion techniques for SLM applications.

Conclusions:

  • The developed microscopic image fusion method is effective for SLM vision systems.
  • The technique successfully overcomes image fuzziness issues in objects with large vertical dimensions.
  • This approach significantly enhances surface profile measurement accuracy and clarity in microscopy.