Real-time target tracking system based on joint transform correlator and neural network algorithm

Eun-Soo Kim; Sang-Yi Yi; Jin-Ho Lee

doi:10.1117/12.131208

30 October 1992 Real-time target tracking system based on joint transform correlator and neural network algorithm

Eun-Soo Kim, Sang-Yi Yi, Jin-Ho Lee

Proceedings Volume 1812, Optical Computing and Neural Networks; (1992) https://doi.org/10.1117/12.131208
Event: International Symposium on Optoelectronics in Computers, Communications, and Control, 1992, Hsinchu, Taiwan

Abstract

In this paper, we present a new opto-neural approach to the problem of multi-target tracking. The proposed hybrid opto-neural system uses an optical joint transform correlator to reduce the massive input target data into a few correlation peak signals and then a massive parallel computational neural network algorithm is used for effective target tracking data association based on these correlation signals. For real-time operation, a nonlinear joint transform correlator is optically implemented using a high resolution LCD spatial light modulator (SLM) and a new track based on field (TBF) neural network tracking algorithm is introduced to tackle the effective multi-target data association in a real-time basis. Through the computer simulation, the performance of the proposed hybrid opto-neural tracking system is evaluated and some experimental results on simultaneous tracking of multi-targets are also provided.

Citation Download Citation

Eun-Soo Kim, Sang-Yi Yi, and Jin-Ho Lee "Real-time target tracking system based on joint transform correlator and neural network algorithm", Proc. SPIE 1812, Optical Computing and Neural Networks, (30 October 1992); https://doi.org/10.1117/12.131208

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