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Proceedings Paper

Recognition for TSS-1 satellite body by hybrid neural networks
Author(s): Zhiling Wang; I. Barraco; M. Rovazzotti; F. Raveva; S. DeSanctis
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Paper Abstract

Because of the learning capacity, parallel structure, and tolerant performance of neural networks, we have used hybrid neural networks to recognize the body of a TSS-1 satellite made in Italy. A set of features based on both boundary points and a centroid of the body has been extracted from an image with the satellite body. The features have been proved to be rather stable to the changes of translation, rotation, magnification, and distortion. Therefore, object recognition with higher accuracy has been performed in this paper.

Paper Details

Date Published: 28 March 1995
PDF: 12 pages
Proc. SPIE 2424, Nonlinear Image Processing VI, (28 March 1995); doi: 10.1117/12.205256
Show Author Affiliations
Zhiling Wang, Alenia Spazio SpA and Italian Space Agency (Italy)
I. Barraco, Alenia Spazio SpA (Italy)
M. Rovazzotti, Alenia Spazio SpA (Italy)
F. Raveva, Alenia Spazio SpA (Italy)
S. DeSanctis, Alenia Spazio SpA (Italy)

Published in SPIE Proceedings Vol. 2424:
Nonlinear Image Processing VI
Edward R. Dougherty; Jaakko T. Astola; Harold G. Longbotham; Nasser M. Nasrabadi; Aggelos K. Katsaggelos, Editor(s)

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