1 August 1996 Pattern classification using a joint transform correlator based nearest neighbor classifier
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Optical Engineering, 35(8), (1996). doi:10.1117/1.600798
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.
Guowen Lu, Francis T. S. Yu, "Pattern classification using a joint transform correlator based nearest neighbor classifier," Optical Engineering 35(8), (1 August 1996). http://dx.doi.org/10.1117/1.600798
JOURNAL ARTICLE
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KEYWORDS
Image classification

Optical character recognition

Single crystal X-ray diffraction

Joint transforms

Optical correlators

Optical engineering

Neural networks

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