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Proceedings Paper

Detection of vehicles in infrared imagery using shared-weight neural network feature detectors
Author(s): Dick de Ridder; Klamer Schutte; Piet B. W. Schwering
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Paper Abstract

In this paper, we discuss the possibility of using artificial neural networks (ANNs) as feature detectors in automatic target recognition (ATR). The goal is to discern a vehicle in an infrared image. We train ANNs to recognize the most easily recognizable parts of the vehicles, the wheels. The specific ANNs we use, shared weight ANNs, are especially adept at such an image recognition task due to their specialized architecture. The feature detection stage results in an image containing in each pixel the output of the ANN, indicating its confidence in the classification. We can then use a simple sequence of image processing algorithms on this image to find peaks and, by counting the number of these peaks, vehicles. This system is tested on sensitivity to scale differences and background clutter and is shown to perform quite well.

Paper Details

Date Published: 17 July 1998
PDF: 12 pages
Proc. SPIE 3374, Signal Processing, Sensor Fusion, and Target Recognition VII, (17 July 1998); doi: 10.1117/12.327104
Show Author Affiliations
Dick de Ridder, Delft Univ. of Technology (Netherlands)
Klamer Schutte, TNO Physics and Electronics Lab. (Netherlands)
Piet B. W. Schwering, TNO Physics and Electronics Lab. (Netherlands)

Published in SPIE Proceedings Vol. 3374:
Signal Processing, Sensor Fusion, and Target Recognition VII
Ivan Kadar, Editor(s)

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