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EURASIP Journal on Advances in Signal Processing
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Automatic Target Recognition in Synthetic Aperture Sonar Images Based on Geometrical Feature Extraction

EURASIP Journal on Advances in Signal Processing volume 2009, Article number: 109438 (2009) Cite this article

Abstract

This paper presents a new supervised classification approach for automated target recognition (ATR) in SAS images. The recognition procedure starts with a novel segmentation stage based on the Hilbert transform. A number of geometrical features are then extracted and used to classify observed objects against a previously compiled database of target and non-target features. The proposed approach has been tested on a set of 1528 simulated images created by the NURC SIGMAS sonar model, achieving up to 95% classification accuracy.

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Authors and Affiliations

  1. NATO Undersea Research Centre (NURC), 19126, La Spezia, Italy

    J. Del Rio Vera, E. Coiras, J. Groen & B. Evans

  2. ESRIN, European Space Agency (ESA), 00044, Frascati, Italy

    J. Del Rio Vera

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  1. J. Del Rio Vera
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  2. E. Coiras
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  3. J. Groen
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  4. B. Evans
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Corresponding author

Correspondence to J. Del Rio Vera.

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Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License (https://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Del Rio Vera, J., Coiras, E., Groen, J. et al. Automatic Target Recognition in Synthetic Aperture Sonar Images Based on Geometrical Feature Extraction. EURASIP J. Adv. Signal Process. 2009, 109438 (2009). https://doi.org/10.1155/2009/109438

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  • DOI: https://doi.org/10.1155/2009/109438

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