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Proceedings Paper

Guidance in feature extraction to resolve uncertainty
Author(s): Boris Kovalerchuk; Michael Kovalerchuk; Simon Streltsov; Matthew Best
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Paper Abstract

Automated Feature Extraction (AFE) plays a critical role in image understanding. Often the imagery analysts extract features better than AFE algorithms do, because analysts use additional information. The extraction and processing of this information can be more complex than the original AFE task, and that leads to the “complexity trap”. This can happen when the shadow from the buildings guides the extraction of buildings and roads. This work proposes an AFE algorithm to extract roads and trails by using the GMTI/GPS tracking information and older inaccurate maps of roads and trails as AFE guides.

Paper Details

Date Published: 13 June 2013
PDF: 12 pages
Proc. SPIE 8747, Geospatial InfoFusion III, 874707 (13 June 2013); doi: 10.1117/12.2016509
Show Author Affiliations
Boris Kovalerchuk, Central Washington Univ. (United States)
BKF Systems (United States)
Michael Kovalerchuk, BKF Systems (United States)
Simon Streltsov, LongShort Way Inc. (United States)
Matthew Best, U.S. Air Force (United States)


Published in SPIE Proceedings Vol. 8747:
Geospatial InfoFusion III
Matthew F. Pellechia; Richard J. Sorensen; Kannappan Palaniappan, Editor(s)

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