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Proceedings Paper

Neural networks-based face recognition using Fourier plane nonlinear filters
Author(s): Bahram Javidi; Jian Li
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Paper Abstract

We describe a nonlinear joint transform correlator-based two-layer network that uses a supervised learning algorithm for real-time face recognition. The system is trained with a sequence of facial images and is able to classify an input face image in real-time. Computer simulations and optical experimental results are presented. The processor can be manufactured into a compact low-cost optoelectronic system. The use of the nonlinear joint transform correlator provides good noise robustness and good image discrimination.

Paper Details

Date Published: 28 August 1995
PDF: 10 pages
Proc. SPIE 2565, Optical Implementation of Information Processing, (28 August 1995); doi: 10.1117/12.217666
Show Author Affiliations
Bahram Javidi, Univ. of Connecticut (United States)
Jian Li, Univ. of Connecticut (United States)


Published in SPIE Proceedings Vol. 2565:
Optical Implementation of Information Processing
Bahram Javidi; Joseph L. Horner, Editor(s)

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