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Model Agnostic Extreme Sub-pixel Visual Measurement and Optimal Characterization

Abstract It is possible in a properly controlled environment, such as industrial metrology, to make significant headway into the non-industrial constraints on image-based position measurement using the techniques of image registration and achieve repeatable feature measurements on the order of 0.3% of a pixel, or about an order of magnitude improvement on conventional real-world performance. These measurements are then used as inputs for a model optimal, model agnostic, smoothing for calibration of a laser scribe and online tracking of velocimeter using video input. Using appropriate smooth interpolation to increase effective sample density can reduce uncertainty and improve estimates. Use of the proper negative offset of the template function has t... (more)
Created Date 2012
Contributor Munroe, Michael R. (Author) / Phelan, Patrick (Advisor) / Kostelich, Eric (Committee member) / Mahalov, Alex (Committee member) / Arizona State University (Publisher)
Subject Mechanical engineering / Compressed Sensing / Inverse Modeling / Kalman Filtering / Photogrammetry / Subpixel Metrology / System Identification
Type Masters Thesis
Extent 66 pages
Language English
Reuse Permissions All Rights Reserved
Note M.S. Mechanical Engineering 2012
Collaborating Institutions Graduate College / ASU Library
Additional Formats MODS / OAI Dublin Core / RIS

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Description Dissertation/Thesis
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Description Measurement Results (part 1)
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Description Measurement Results (part 2)
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Description General Presentation