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
Ronald Wu and Henry Stark, "Rotation-invariant pattern recognition using optimum feature extraction," Appl. Opt. 24, 179-184 (1985)