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.
© 1995 Optical Society of America
Full Article | PDF ArticleMore Like This
A. Alsamman and Mohammad S. Alam
Appl. Opt. 44(5) 688-692 (2005)
Eriko Watanabe and Kashiko Kodate
Appl. Opt. 44(5) 666-676 (2005)
Shuqun Zhang and Mohammad A. Karim
Appl. Opt. 38(5) 847-854 (1999)