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Proceedings Paper

Multi-object intensity-invariant pattern recognition with an optimal processor for correlated noise
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Paper Abstract

Normalized correlation provides a way to achieve reliable pattern recognition with images containing multiple target objects of unequal intensities without the need of image segmentation. We show that the optimum Bayesian processor for the detection of a target with additive correlated noise and disjoint background, introduced, has the form of the normalized correlation. In consequence it can be expressed with correlations and pointwise processing only--which is a condition for an efficient optical implementation. Moreover it may be applied to multi-object intensity invariant problems.

Paper Details

Date Published: 19 July 1999
PDF: 2 pages
Proc. SPIE 3749, 18th Congress of the International Commission for Optics, (19 July 1999); doi: 10.1117/12.354765
Show Author Affiliations
Rafal Kotynski, Warsaw Univ. (Poland)
Katarzyna Chalasinska-Macukow, Warsaw Univ. (Poland)


Published in SPIE Proceedings Vol. 3749:
18th Congress of the International Commission for Optics
Alexander J. Glass; Joseph W. Goodman; Milton Chang; Arthur H. Guenther; Toshimitsu Asakura, Editor(s)

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