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Proceedings Paper

Practical target recognition in infrared imagery using a neural network
Author(s): Alistair A. Crowe; A. Patel; William A. Wright; Michael Antony Green; Andrew David Hughes
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Paper Abstract

This paper describes work undertaken by British Aerospace (BAe) on the development of a neural network classifier for automatic recognition of land based targets in infrared imagery. The classifier used a histogram segmentation process to extract regions from the infrared imagery. A set of features were calculated for each region to form a feature vector describing the region. These feature vectors were then used as the input to the neural classifier. Two neural classifiers were investigated based upon the multi-layer perceptron and radial basis function networks. In order to assess the merits of a neural network approach, the neural classifiers were compared with a conventional classifier originally developed by British Aerospace (Systems and Equipment) Ltd., under contract to RARDE (Chertsey), for the purpose of infrared target recognition. This conventional system was based upon a Schurman classifier which operates on data transformed using a Hotelling Trace Transform. The ability of the classifiers to perform practical recognition of real-world targets was evaluated by training and testing the classifiers on real imagery obtained from mock land battles and military vehicle trials.

Paper Details

Date Published: 9 July 1992
PDF: 12 pages
Proc. SPIE 1699, Signal Processing, Sensor Fusion, and Target Recognition, (9 July 1992); doi: 10.1117/12.138228
Show Author Affiliations
Alistair A. Crowe, British Aerospace Corp. (United Kingdom)
A. Patel, British Aerospace Corp. (United Kingdom)
William A. Wright, British Aerospace Corp. (United Kingdom)
Michael Antony Green, British Aerospace Systems and Equipment Ltd. (United Kingdom)
Andrew David Hughes, British Aerospace Systems and Equipment Ltd. (United Kingdom)


Published in SPIE Proceedings Vol. 1699:
Signal Processing, Sensor Fusion, and Target Recognition
Vibeke Libby; Ivan Kadar, Editor(s)

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