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Measuring the Complete-arch Distortion of an Optical Dental Impression

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A Novel Method for Optical Distortion Quantification.

Katherine M Gerton¹, Brenda J Novar², William Brockmeier³

¹Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, New Jersey.

Optometry and Vision Science : Official Publication of the American Academy of Optometry

|December 28, 2018

Summary

A new quantitative method precisely measures optical distortion in transparent materials, identifying distortions as low as 0.1%. This advanced technique improves upon qualitative assessments for Air Force visor evaluations.

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Area of Science:

Optics and Materials Science
Image Processing and Analysis
Human Factors Engineering

Background:

Optical distortion degrades visual targets, a critical issue for transparent materials like Air Force visors.
Current evaluation methods for optical distortion are qualitative, lacking consistency and precise measurement capabilities.
Military standards (MIL-DTL-43511D) exist, but the assessment of distortion is subjective, with a 3% fabrication tolerance limit.

Purpose of the Study:

To develop a novel, quantitative technique for assessing optical distortion in transparent materials.
To overcome the limitations of current qualitative evaluation methods used by the Air Force.
To establish a more consistent and reliable method for measuring distortion acceptability.

Main Methods:

Modification of a standard optical tester for distortion pattern analysis.
Development of an image-processing algorithm to mathematically analyze Ronchi grid distortion patterns.
Utilizing two-dimensional median filtering on digital images for high-resolution distortion mapping.

Main Results:

A refined algorithm enabled standardized creation of high-resolution optical distortion maps.
The technique achieved a resolution capability of 0.10% distortion.
Image processing allowed for enhanced contrast and precise measurement of distortion in small areas.

Conclusions:

Quantifying optical distortion is crucial for understanding its impact on human visual performance.
This quantitative approach provides a foundation for objective visual performance metric development.
Future research will correlate distortion characteristics with empirical human visual performance data.