Abstract

We describe a pattern recognition processor based on a new optimal ${\chi }^2$ filtering method that is designed to localize a target with unknown gray levels appearing on a random background. This processor consists of preprocessing of the analyzed image followed by correlations with binary masks.

© 1997 Optical Society of America

Optimal detection of a target with random gray levels on a spatially disjoint background noise

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Unified statistically independent region processor for deterministic and fluctuating targets in nonoverlapping background

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Improvement in robustness of the statistically independent region snake-based segmentation method of target-shape tracking

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Optimal target tracking on image sequences with a deterministic background

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