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Proceedings Paper

Edge detection and image segmentation of space scenes using fractal analyses
Author(s): Timothy F. Cleghorn; J. Joseph Fuller
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Paper Abstract

Most of the development work on automated Machine Vision for space operations has assumed the presence of a dark sky background or a 'cooperative', (i.e.: marked or lighted), target. In reality, the sun-lit earth, or other natural body, will be the background much of the time, providing a far more difficult image segmentation problem. Fortunately, many of the natural background objects, e.g.: clouds, mountain ranges, etc., exhibit fractal characteristics when viewed from orbit. Images of manmade objects such as satellites, space shuttles, and stations will yield sufficiently different values for the fractal parameters so that edge detection and segmentation can be accomplished. This paper describes the methods used to segment images of space scenes into manmade and natural components using fractal dimensions and lacunarities. The calculation of these parameters are described in detail, and the results presented for a variety of aerospace images.

Paper Details

Date Published: 1 October 1992
PDF: 9 pages
Proc. SPIE 1705, Visual Information Processing, (1 October 1992); doi: 10.1117/12.138474
Show Author Affiliations
Timothy F. Cleghorn, NASA/Johnson Space Ctr. (United States)
J. Joseph Fuller, West Virginia Institute of Technology (United States)

Published in SPIE Proceedings Vol. 1705:
Visual Information Processing
Friedrich O. Huck; Richard D. Juday, Editor(s)

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