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Proceedings Paper

Target identification by means of adaptive neural networks in thermal infrared images
Author(s): Marc P. J. Acheroy; Wim Mees
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Paper Abstract

A generic method for target recognition is presented. The stress is put on the methods based on the neural networks and more specifically on the adaptive resonance theory (ART) models. This type of artificial neural network (ANN) has the advantage of being unsupervised and adaptive: it is indeed able to acquire and adapt its long-term memory taking into account the context evolution. ART networks very quickly recognize classes that are already known, they also learn new images very fast. Two versions of ART are investigated: ART1, which only works with binary data, and ART2, which is working with analog data. In practice, ART1 seems to need larger images than ART2 to achieve the same efficiency, but is obviously faster. A preprocessor has been developed whose output is invariant to translation, rotation, and scale changes of the input. The most important feature of this preprocessor is its ability to preserve visual interpretation, which is not the case for the more classical methods using Fourier-like and log/polar transforms.

Paper Details

Date Published: 1 October 1991
PDF: 12 pages
Proc. SPIE 1569, Stochastic and Neural Methods in Signal Processing, Image Processing, and Computer Vision, (1 October 1991); doi: 10.1117/12.48372
Show Author Affiliations
Marc P. J. Acheroy, Royal Military Academy (Belgium)
Wim Mees, Royal Military Academy (Belgium)

Published in SPIE Proceedings Vol. 1569:
Stochastic and Neural Methods in Signal Processing, Image Processing, and Computer Vision
Su-Shing Chen, Editor(s)

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