Abstract

In this paper we consider the problem of detecting a target regardless of its orientation when it is known that the target must be from one of two classes. We assume significant random intraclass variability, a complication which requires techniques from statistical pattern recognition for amelioration. The Foley-Sammon transformation for selecting optimum features from random training samples is used to solve the problem.

© 1985 Optical Society of America

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