Real-time compact optoelectronic neural networks for face recognition

Bahram Javidi; Jian Li

doi:10.1117/12.243104

14 June 1996 Real-time compact optoelectronic neural networks for face recognition

Bahram Javidi, Jian Li

Proceedings Volume 2749, Photonic Component Engineering and Applications; (1996) https://doi.org/10.1117/12.243104
Event: Aerospace/Defense Sensing and Controls, 1996, Orlando, FL, United States

Abstract

We describe a nonlinear joint transform correlator-based two-layer neural 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.

Citation Download Citation

Bahram Javidi and Jian Li "Real-time compact optoelectronic neural networks for face recognition", Proc. SPIE 2749, Photonic Component Engineering and Applications, (14 June 1996); https://doi.org/10.1117/12.243104

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