Identification of man-made regions in unmanned aerial vehicleimagery and videos
Solka, J.L.
Marchette, D.J.
Wallet, B.C.
Irwin, V.L.
Rogers, G.W.
Adv. Comput. Technol. Group, Naval Surface Warfare Center, Dahlgren, VA;
This paper appears in: Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publication Date: Aug 1998
Volume: 20,
Issue: 8
On page(s): 852-857
ISSN: 0162-8828
References Cited: 15
CODEN: ITPIDJ
INSPEC Accession Number: 6018670
Digital Object Identifier: 10.1109/34.709607
Current Version Published: 2002-08-06
Abstract
Details work in our group on the use of low-level features for the
identification of man-made regions in unmanned aerial vehicle (UAV)
imagery. The feature sets that we have examined include classical
statistical features such as the coefficient of variation in a window
about a pixel, locally computed fractal dimension, and fractal dimension
computed in the presence of wavelet boundaries. We discuss these
techniques of feature extraction along with our approach to the
classification of the features. Our classification work has focused on
the use of a semiparametric probability density estimation technique. In
addition, we present classification results for region of interest
identification based on a set of test images from an UAV test flight
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