Recognition for TSS-1 satellite body by hybrid neural networks

Zhiling Wang; I. Barraco; M. Rovazzotti; F. Raveva; S. DeSanctis

doi:10.1117/12.205256

28 March 1995 Recognition for TSS-1 satellite body by hybrid neural networks

Zhiling Wang, I. Barraco, M. Rovazzotti, F. Raveva, S. DeSanctis

Proceedings Volume 2424, Nonlinear Image Processing VI; (1995) https://doi.org/10.1117/12.205256
Event: IS&T/SPIE's Symposium on Electronic Imaging: Science and Technology, 1995, San Jose, CA, United States

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.

Citation Download Citation

Zhiling Wang, I. Barraco, M. Rovazzotti, F. Raveva, and S. DeSanctis "Recognition for TSS-1 satellite body by hybrid neural networks", Proc. SPIE 2424, Nonlinear Image Processing VI, (28 March 1995); https://doi.org/10.1117/12.205256

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