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Proceedings Paper

Distortion-invariant pattern recognition using composite Fourier plane nonlinear filtering
Author(s): Bahram Javidi; Wenlu Wang; Guanshen Zhang
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Paper Abstract

In this paper we investigate composite Fourier-plane nonlinear filters for distortion invariant pattern recognition. Different types of noise such as spatially non-overlapping color background noise, other non-target object, real scene noise, and additive white noise are used to investigate the performance of the filter. Computer simulation results are presented to show the performance enhancement using Fourier-plane nonlinearities in the composite filter designs. The training image sets and the test image sets are generate by in-plane and out-plane rotation of different aircraft.

Paper Details

Date Published: 24 October 1997
PDF: 16 pages
Proc. SPIE 3159, Algorithms, Devices, and Systems for Optical Information Processing, (24 October 1997); doi: 10.1117/12.284203
Show Author Affiliations
Bahram Javidi, Univ. of Connecticut (United States)
Wenlu Wang, Univ. of Connecticut (United States)
Guanshen Zhang, Univ. of Connecticut (United States)

Published in SPIE Proceedings Vol. 3159:
Algorithms, Devices, and Systems for Optical Information Processing
Bahram Javidi; Demetri Psaltis, Editor(s)

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