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Proceedings Paper

A Hierarchical Control Strategy For 2-D Object Recognition
Author(s): Mark F. Cullen; Christopher L. Kuszmaul; Timothy S. Ramsey
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Paper Abstract

A control strategy for 2-D object recognition has been implemented on a hardware configuration which includes a Symbolics Lisp Machine (TM) as a front-end processor to a 16,384 processor Connection Machine (TM). The goal of this ongoing research program is to develop an image analysis system as an aid to human image interpretation experts. Our efforts have concentrated on 2-D object recognition in aerial imagery specifically, the detection and identification of aircraft near the Danbury, CT airport. Image processing functions to label and extract image features are implemented on the Connection Machine for robust computation. A model matching function was also designed and implemented on the CM for object recognition. In this paper we report on the integration of these algorithms on the CM, with a hierarchical control strategy to focus and guide the object recognition task to particular objects and regions of interest in imagery. It will be shown that these tech-nigues may be used to manipulate imagery on the order of 2k x 2k pixels in near-real-time.

Paper Details

Date Published: 19 February 1988
PDF: 5 pages
Proc. SPIE 0848, Intelligent Robots and Computer Vision VI, (19 February 1988); doi: 10.1117/12.942739
Show Author Affiliations
Mark F. Cullen, Perkin-Elmer Corporation (United States)
Christopher L. Kuszmaul, Perkin-Elmer Corporation (United States)
Timothy S. Ramsey, Perkin-Elmer Corporation (United States)

Published in SPIE Proceedings Vol. 0848:
Intelligent Robots and Computer Vision VI
David P. Casasent; Ernest L. Hall, Editor(s)

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