Visual pattern recognition using coupled filters

Stanley E. Monroe Jr.; Richard D. Juday; R. Shane Barton; Michael K. Qin

doi:10.1117/12.212750

30 June 1995 Visual pattern recognition using coupled filters

Stanley E. Monroe Jr., Richard D. Juday, R. Shane Barton, Michael K. Qin

Proceedings Volume 2463, Synthetic Vision for Vehicle Guidance and Control; (1995) https://doi.org/10.1117/12.212750
Event: SPIE's 1995 Symposium on OE/Aerospace Sensing and Dual Use Photonics, 1995, Orlando, FL, United States

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.

Citation Download Citation

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); https://doi.org/10.1117/12.212750

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