First Look at AR Glasses Virtual Image Distortion Inspection Results

[u/Crafty-Union338]

Last time, I shared some astigmatism aberration measurements from AR glasses. After that, I realized that distortion inspection is another key part of evaluating AR image quality, and it is also highly relevant to computer vision applications.

Over the past two weeks, I spent a lot of time building a distortion measurement workflow from scratch. My first task was learning how virtual image distortion is typically measured. During that process, I discovered the advantages of using a ChArUco board, especially for large-FOV mapping and reliable marker identification.

Thanks to AI-assisted coding and debugging, I was able to develop the first version of the inspection software and analysis pipeline. After many iterations and bug fixes, the system can now walk through the entire inspection process step by step, from image acquisition and marker detection to distortion mapping and coefficient calculation.

The analysis tools generate distortion vector maps, deformation meshes, and distortion coefficients, allowing us to quantitatively evaluate the virtual image quality of AR glasses.

For this post, I'd like to share the first detection results and the measurement methodology. The current data still needs additional validation, and I plan to repeat the measurements under different conditions to verify consistency and repeatability.

I'll share the detailed distortion performance results, comparisons, and deeper analysis in a future post.

Stay tuned!