9 July 1992 Practical target recognition in infrared imagery using a neural network
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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.
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Alistair A. Crowe, Alistair A. Crowe, A. Patel, A. Patel, William A. Wright, William A. Wright, Michael Antony Green, Michael Antony Green, Andrew David Hughes, Andrew David Hughes, } "Practical target recognition in infrared imagery using a neural network", Proc. SPIE 1699, Signal Processing, Sensor Fusion, and Target Recognition, (9 July 1992); doi: 10.1117/12.138228; https://doi.org/10.1117/12.138228
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