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Proceedings Paper

Application of an image feature network-based object recognition algorithm to aircraft detection and classification
Author(s): Jeremy Straub
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Paper Abstract

A network created from the distance-values representing the spacing between points identified by an image feature detection algorithm can be utilized for object classification. This paper presents work on the application of this algorithm to the problem of aircraft presence detection and classification. It considers algorithm performance across a variety of scenarios, including instances where the sky has different characteristics, detection and characterization from different levels of image resolution and detection and characterization where multiple craft are present in a single frame. An extension to the base algorithm, which determines the orientation of a detected aircraft is also presented.

Paper Details

Date Published: 13 June 2014
PDF: 6 pages
Proc. SPIE 9090, Automatic Target Recognition XXIV, 909005 (13 June 2014); doi: 10.1117/12.2050172
Show Author Affiliations
Jeremy Straub, The Univ. of North Dakota (United States)


Published in SPIE Proceedings Vol. 9090:
Automatic Target Recognition XXIV
Firooz A. Sadjadi; Abhijit Mahalanobis, Editor(s)

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