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A Machine Vision System for Automated Measurement and Assessment of Optical Distortion in Aircraft Transparencies

Michael Dixon, Robert Glaubius, Philip Freeman, Robert Pless, Michael Gleason, Matthew Thomas, and William D. Smart.
Machine Vision and Applications 22(5), Springer, 2011.

We describe a complete system for quantitatively measuring the optical distortion in aircraft windscreens and automatically classifying that distortion as acceptable or not. The system is comprised of two parts: the first uses digital imaging of a known grid pattern through the windshield of interest to create a distortion map of that windshield. The second part uses the distortion maps created for 60 windshields (some acceptable and some not) and automatically learns a decision-tree based classifier. We show results that highlight the robustness of this system, including a demonstration that the distortion map for a windshield is consistently measured over 3 years, and cross-validation study shows that we can effectively classify windshields based on the distortion maps.

Paper: [PDF]

@article{mva11,
  author = {Dixon, Michael and Glaubius, Robert and Freeman, Philip and Pless, Robert and Gleason, Michael and Thomas, Matthew and Smart, William D.},
  title = {A Machine Vision System for Automated Measurement and Assessment of Optical Distortion in Aircraft Transparencies},
  journal = {Machine Vision and Applications},
  volume = {22},
  number = {5},
  pages = {791--804},
  publisher = {Springer},
  year = {2011}
}