9 July 1992 Practical target recognition in infrared imagery using a neural network
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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.
© (1992) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
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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