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Proceedings Paper

Visual pattern recognition using coupled filters
Author(s): Stanley E. Monroe; Richard D. Juday; R. Shane Barton; Michael K. Qin
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Paper Abstract

We discuss the use of an optical correlator with a highly coupled filter and dappled targets to track an object in a field of view cluttered by background noise and/or similar objects. The dappled targets are fractal images whose statistics are independent of scale. Each is unique for tracking the targets. We report the drop in correlation (hence recognition) of an object as a function of in-plane rotation and as a function of range. We discuss plans for an application in Johnson Space Center's Automation and Robotics group, in which correlation processing of these targets would distinguish an object and pass its position and orientation to a robot control system. Using MEDOF (minimum Euclidean distance optimal filter) to create filters on the coupled filter modulator, we show that background clutter can be optically filtered out.

Paper Details

Date Published: 30 June 1995
PDF: 7 pages
Proc. SPIE 2463, Synthetic Vision for Vehicle Guidance and Control, (30 June 1995); doi: 10.1117/12.212750
Show Author Affiliations
Stanley E. Monroe, Lockheed Engineering and Sciences Co. (United States)
Richard D. Juday, NASA Johnson Space Ctr. (United States)
R. Shane Barton, NASA Johnson Space Ctr. (United States)
Michael K. Qin, NASA Johnson Space Ctr. (United States)

Published in SPIE Proceedings Vol. 2463:
Synthetic Vision for Vehicle Guidance and Control
Jacques G. Verly, Editor(s)

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