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Proceedings Paper

Target representation and classification using random graphs
Author(s): Firooz Sadjadi
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Paper Abstract

In this paper a novel method is described for representation and classification of target by random graphs. A target is represented in terms of set primitives that jointly represent a random graph structure. Random graph is a graph structure with randomly varying vertex and arc attribute values. Random graphs and their statistical and matrix representations are useful when one encounters the problem of classifying signatures of partially occluded targets. We present a number of observations that spectra of random graphs of partially occluded and non-occluded target signatures are related through an interlacing rule and the correlations of their Laplacians lead to robust classification.

Paper Details

Date Published: 12 May 2016
PDF: 9 pages
Proc. SPIE 9844, Automatic Target Recognition XXVI, 98440I (12 May 2016); doi: 10.1117/12.2239902
Show Author Affiliations
Firooz Sadjadi, Lockheed Martin Technology Labs. (United States)


Published in SPIE Proceedings Vol. 9844:
Automatic Target Recognition XXVI
Firooz A. Sadjadi; Abhijit Mahalanobis, Editor(s)

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