Neural network real time video processor for early aircraft detection

Authors:
Gregory Hauser;Milos Manic
Affiliations:
Department of Electrical & Computer Engineering, University of Idaho at Moscow, Moscow, Idaho;Department of Computer Science, University of Idaho at Idaho Falls, Idaho Falls, Idaho
Venue:
ETFA'09 Proceedings of the 14th IEEE international conference on Emerging technologies & factory automation
Year:
2009

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Abstract

Detecting an aircraft solely by its infrared (IR) signature in real time can be extremely challenging task depending on the image background clutter. Neural networks offer a reliable method of detecting targets (aircraft) against a multitude of background scenes and a variety of environmental conditions. Neural networks can rapidly "learn" to differentiate between background clutter and fast moving, small, "hot" (temperature) targets. A Neural Network Real Time Video Processor (NN-RTVP) presented in this paper was inspired by and a Kohonen Neural Network (KNN) approach to not only process "still" frames but also process video in real time. Experimental results demonstrated that it is possible to provide real time "point-outs" of thermally significant objects.