Three different linear transformations have been examined for their potential use as feature extractors for an automatic target recognition classifier. These transformations are based on a set of eigen targets, which are obtained through one of the following three methods: principal component analysis, the eigen separation transform, or the Fisher linear discriminant. From the sets of eigen targets obtained through each of the above methods, projection values of an input image are computed and fed to one or more multilayer perceptrons (MLPs) for training and testing purposes. With a fixed-structure MLP, each of the different eigen target sets are examined for their effects on the final recognition performance.

Date Published: 18 September 1998
PDF: 12 pages
Proc. SPIE 3371, Automatic Target Recognition VIII, (18 September 1998); doi: 10.1117/12.323853

Published in SPIE Proceedings Vol. 3371:
Automatic Target Recognition VIII
Firooz A. Sadjadi, Editor(s)