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Proceedings Paper

Optical Implementation Of High-Speed Pattern Recognition
Author(s): H. H. Arsenault; G. April; A. Bergeron; V. Francois; L. Leclerc; Y. Sheng
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Paper Abstract

The capability of Optics to carry out operations in parallel on large masses of data has fueled the current interest in many areas of Optics. However many of the Optical methods proposed have so far only been implemented in digital simulations. Some new or recently implemented methods for invariant pattern recognition will be reviewed, and the problems associated with implementing them with Optics will be discussed. Some of the methods discussed will include pattern recognition with advanced invariant matched filters designed to enhance classification performance and reduce sidelobes and the effects of noise and clutter; neural network content-addressable memories and symbolic substitution systems; and neural logic modules and their combinations with other neural networks to carry out fuzzy logic operations. The optical implementation of the above exemples and of some others will be discussed. In particular, a new representation of 2-D objects that represents any object by a small number of coefficients with invariant (rotation and scale) properties will be introduced, a method to realize it optically will be described, and its combination with a neural network to accomplish invariant pattern classification will be proposed.

Paper Details

Date Published: 25 October 1989
PDF: 5 pages
Proc. SPIE 1134, Optical Pattern Recognition II, (25 October 1989); doi: 10.1117/12.961632
Show Author Affiliations
H. H. Arsenault, Universite Laval (Canada)
G. April, Universite Laval (Canada)
A. Bergeron, Universite Laval (Canada)
V. Francois, Universite Laval (Canada)
L. Leclerc, Universite Laval (Canada)
Y. Sheng, Universite Laval (Canada)

Published in SPIE Proceedings Vol. 1134:
Optical Pattern Recognition II
H. John Caulfield, Editor(s)

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