Exploiting sub-pixel edge detection methods with high-density sampling to provide .001 pixels rigid target localization

Jeffrey F. Gray

doi:10.1117/12.739318

2 May 2007 Exploiting sub-pixel edge detection methods with high density sampling to provide .001 pixels rigid target localization

Jeffrey F. Gray

Author Affiliations +

Proceedings Volume 6579, Mobile Multimedia/Image Processing for Military and Security Applications 2007; 65790X (2007) https://doi.org/10.1117/12.739318
Event: Defense and Security Symposium, 2007, Orlando, Florida, United States

Abstract

An empirical method for Canny filter optimization is explored and applied to the problem of measuring rigid motion between targets for nanometer motion detection. Operating with an image space pixel size of 3 μm, we are able to obtain static target localization to 6 nm at 2σ variation. To discriminate target roughness from sub-pixel measurement noise we use a Laplacian filter method. To extend the resolution beyond the limits of a single sub-pixel sample we use multiple adjacent edge locations along a single target to statistically reduce the overall resolution. With sufficient samples we obtain near .001 pixels resolving power. Even at this resolution we have not reached the limits of sampling which are possible from simultaneously sampling sets of parallel lines allowing for future refinement of method to localize well below .001 pixels.

Citation Download Citation

Jeffrey F. Gray "Exploiting sub-pixel edge detection methods with high density sampling to provide .001 pixels rigid target localization", Proc. SPIE 6579, Mobile Multimedia/Image Processing for Military and Security Applications 2007, 65790X (2 May 2007); https://doi.org/10.1117/12.739318

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