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30 June 1995 Visual pattern recognition using coupled filters
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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.
© (1995) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Stanley E. Monroe Jr., Richard D. Juday, R. Shane Barton, and Michael K. Qin "Visual pattern recognition using coupled filters", Proc. SPIE 2463, Synthetic Vision for Vehicle Guidance and Control, (30 June 1995);

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