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Optical Engineering

An optical correlator feature extractor neural net system
Author(s): David P. Casasent
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Paper Abstract

The three optical information processing techniques of detection, recognition, and identification can and should be combined to achieve the best benefits of each. All methods are required for difficult pattern recognition problems. We consider the identification of multiple objects in the field of view in clutter. A morphological correlator is used to achieve detection. Hierarchical and symbolic pattern recognition correlators can also achieve detection as well as recognition. For very large class probems, feature extractors are required for identification, but first require detection. For difficult multiclass discrimination problems, neural net methods (rather than linear discriminant functions) are needed for identification.

Paper Details

Date Published: 1 May 1992
PDF: 8 pages
Opt. Eng. 31(5) doi: 10.1117/12.57138
Published in: Optical Engineering Volume 31, Issue 5
Show Author Affiliations
David P. Casasent, Carnegie Mellon Univ. (United States)

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