- Research Article
- Open Access
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)
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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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
- Feature Extraction
- Classification Accuracy
- Quantum Information
- Geometrical Feature