Recognition for TSS-1 satellite body by hybrid neural networks
Zhiling Wang, I. Barraco, M. Rovazzotti, F. Raveva, S. DeSanctis · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1995
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.