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Optical Engineering

Pattern classification using a joint transform correlator based nearest neighbor classifier
Author(s): Guowen Lu; Francis T. S. Yu
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Paper Abstract

A JTC-based nearest neighbor classifier (JTC-NNC) is presented, by which shift-invariant pattern classification can be obtained. To efficiently utilize the spatial domain input plane, a non-zero-order JTC is introduced to remove the autocorrelation power spectra. In addition, a phase-transform technique is introduced into the JTC-NNC to improve the light efficiency and pattern discriminability. Finally, application of the JTC-NNC to optical character recognition is discussed, and computer simulation is provided to show the feasibility of the JTC-NNC.

Paper Details

Date Published: 1 August 1996
PDF: 9 pages
Opt. Eng. 35(8) doi: 10.1117/1.600798
Published in: Optical Engineering Volume 35, Issue 8
Show Author Affiliations
Guowen Lu, The Pennsylvania State Univ. (United States)
Francis T. S. Yu, The Pennsylvania State Univ. (United States)


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