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Updated: Mar 16, 2026

High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques

High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques

Published on: December 3, 2013

Online Wear Detection Using High-Speed Imaging.

Seyfollah Soleimani¹, Jacob Sukumaran², Koen Douterloigne³

¹1Department of Computer Engineering, Faculty of Engineering,Arak University,Arak 38156-8-8349,Iran.

Microscopy and Microanalysis : the Official Journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada

|August 13, 2016

Summary

This summary is machine-generated.

This study demonstrates micro-level change detection on a rotating specimen by analyzing image blur caused by wear. Computer vision successfully tracked surface changes despite challenging imaging conditions.

Keywords:

Rolling-sliding micro-scale abrasion optical microscopy surface analysis

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Area of Science:

Materials Science
Optical Engineering
Computer Vision

Background:

Micro-level wear analysis is crucial for material performance.
Acquiring images of rotating specimens presents significant defocusing challenges.
Image blur can serve as an indicator of material wear during rotation.

Purpose of the Study:

To develop and validate a method for micro-level change detection on a fast-rotating specimen.
To investigate the correlation between image defocusing and material wear.
To demonstrate the capability of computer vision in tracking surface modifications under dynamic conditions.

Main Methods:

Acquisition of microscopic images of a rotating specimen without stopping its motion.
Utilizing image blur as a quantitative measure of specimen diameter change due to wear.
Employing image stitching techniques to analyze larger surface areas.
Applying computer vision algorithms for change detection and surface tracking.

Main Results:

Detected a specimen diameter change of approximately 1.2 µm.
Successfully tracked specific surface locations despite image blurring and uneven illumination.
Demonstrated the feasibility of analyzing material modification on a rotating object.

Conclusions:

Image blur analysis is a viable method for micro-level wear detection in rotating components.
Computer vision techniques can effectively monitor material changes on dynamic surfaces.
Advanced imaging and processing methods enable detailed analysis of material modification at high rotation speeds.