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Proceedings Paper

Feature distributions and probability of identification
Author(s): David M. Doria
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Paper Abstract

In this paper we present a method of analysis of model based automatic target recognition (ATR) algorithms, as a function of a number of important parameters of the system, including the number and size of the models, the correlations between models, the expected probability of detection of features, the rates of occurrence of unpredicted features, and the spatial resolution of the predicted features, as defined by a local spatial feature density. Analytical results for a two class problem are presented as a function of between-class correlation and feature localization accuracy.

Paper Details

Date Published: 13 August 1999
PDF: 10 pages
Proc. SPIE 3721, Algorithms for Synthetic Aperture Radar Imagery VI, (13 August 1999); doi: 10.1117/12.357695
Show Author Affiliations
David M. Doria, Raytheon Systems Co. (United States)


Published in SPIE Proceedings Vol. 3721:
Algorithms for Synthetic Aperture Radar Imagery VI
Edmund G. Zelnio, Editor(s)

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