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Proceedings Paper

Image exploitation using multisensor/neural network systems
Author(s): Edward C. Uberbacher; Y. Xu; R. W. Lee; Charles W. Glover; Martin Beckerman; Reinhold C. Mann
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Paper Abstract

We have developed and evaluated a tool for change detection and other analysis tasks relevant to image exploitation. The tool, visGRAIL, integrates three key elements: (1) the use of multiple algorithms to extract information from images -- feature extractors or 'sensors,' (2) an algorithm to fuse the information -- presently a neural network, and (3) empirical estimation of the fusion parameters based on a representative set of images. The system was applied to test images in the RADIUS common development environment (RCDE). In a task designed to distinguish natural scenes from those containing various amounts of human-made objects and structure, the system classified correctly 95% of 350 images in a test set. This paper describes details of the feature extractors, and presents analyses of the discriminatory characteristics of the features. visGRAIL has been integrated into the RCDE.

Paper Details

Date Published: 19 February 1996
PDF: 12 pages
Proc. SPIE 2645, 24th AIPR Workshop on Tools and Techniques for Modeling and Simulation, (19 February 1996); doi: 10.1117/12.233058
Show Author Affiliations
Edward C. Uberbacher, Oak Ridge National Lab. (United States)
Y. Xu, Oak Ridge National Lab. (United States)
R. W. Lee, Oak Ridge National Lab. (United States)
Charles W. Glover, Oak Ridge National Lab. (United States)
Martin Beckerman, Oak Ridge National Lab. (United States)
Reinhold C. Mann, Oak Ridge National Lab. (United States)


Published in SPIE Proceedings Vol. 2645:
24th AIPR Workshop on Tools and Techniques for Modeling and Simulation
Donald J. Gerson, Editor(s)

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