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Proceedings Paper

Detection of small targets and their characterization based on their formation using an image feature network-based object recognition algorithm
Author(s): Jeremy Straub
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Paper Abstract

Small target detection and classification is problematic. For targets that operate as part of a cluster, classification can be performed based on the characteristics of the cluster’s operations, instead of trying to identify an individual clustermember directly. This paper presents an algorithm for object identification based on comparing networks of point-topoint distances between features identified by an image feature detection algorithm. It discusses the alterations required to make the algorithm suitable for performing cluster-formation based characterization of small targets from point or near-point source data. An analysis of the algorithm’s performance is presented and it efficacy for this application assessed.

Paper Details

Date Published: 13 June 2014
PDF: 6 pages
Proc. SPIE 9092, Signal and Data Processing of Small Targets 2014, 909203 (13 June 2014); doi: 10.1117/12.2050174
Show Author Affiliations
Jeremy Straub, Univ. of North Dakota (United States)


Published in SPIE Proceedings Vol. 9092:
Signal and Data Processing of Small Targets 2014
Oliver E. Drummond, Editor(s)

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