Abstract

Noise insensitivity is one of the most important factors in practical implementations of pattern-recognition systems. Our emphasis is on the recognition of objects in a noisy environment. Spatial filters for distinction between the members of a two-class training set can be designed to achieve minimal error probability in the presence of statistical noise. The filter-design procedure can include additional requirements, such as rotation invariance. Computer simulations demonstrate high class discrimination even in high noise levels that demolish the capability of a human observer to distinguish between the classes.

© 1991 Optical Society of America

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