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Proceedings Paper

Pattern Recognition Using The Ring-Wedge Detector And Neural-Network Software
Author(s): Nicholas George; Shen-ge Wang; D. L. Venable
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Paper Abstract

In pattern recognition and in optical metrology, optical transform systems have been widely applied. Their use is particularly appropriate when the object is detailed and the recognition depends upon features that can be coarsely sampled in the transform space. Now with the advent of neural-network software, it is shown that the major difficulty in applying this optoelectronic hybrid is overcome. Using the ring-wedge photodetector and neural-network software, we illustrate the classification technique using thumbprints. This is a problem of known difficulty to us. Instead of a 4 person-month effort to devise software for its solution, we find that a 4-hour effort is all that is required. Other experiments also discussed are the sorting of photographs of cats and dogs, particulate suspensions, and image quality of digital halftones. All of these are shown to be promising examples for the application of the ring-wedge detector and neural-network software.

Paper Details

Date Published: 25 October 1989
PDF: 12 pages
Proc. SPIE 1134, Optical Pattern Recognition II, (25 October 1989); doi: 10.1117/12.961621
Show Author Affiliations
Nicholas George, University of Rochester (United States)
Shen-ge Wang, University of Rochester (United States)
D. L. Venable, University of Rochester (United States)

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

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