Identification of man-made regions in unmanned aerial vehicle imagery and videos

Author

Solka, J.L. ; Marchette, D.J. ; Wallet, B.C. ; Irwin, V.L. ; Rogers, G.W.

Author_Institution

Adv. Comput. Technol. Group, Naval Surface Warfare Center, Dahlgren, VA, USA

Volume

20

Issue

8

fYear

1998

fDate

8/1/1998 12:00:00 AM

Firstpage

852

Lastpage

857

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

Keywords

feature extraction; fractals; image classification; probability; video signal processing; wavelet transforms; classical statistical features; coefficient of variation; feature extraction; feature sets; features classification; fractal dimension; locally computed fractal dimension; low-level features; man-made regions; semiparametric probability density estimation technique; unmanned aerial vehicle imagery; videos; wavelet boundaries; Buildings; Feature extraction; Fractals; Humans; Image recognition; Machine vision; Remotely operated vehicles; Testing; Unmanned aerial vehicles; Videos;

fLanguage

English

Journal_Title

Pattern Analysis and Machine Intelligence, IEEE Transactions on

Publisher

ieee

ISSN

0162-8828

Type

jour

DOI

10.1109/34.709607

Filename

709607