Automatic Target Recognition in Synthetic Aperture Sonar Images Based on Geometrical Feature Extraction. (6th April 2009)

• Record Type: Journal Article
• Authors: Del Rio Vera, J.; Coiras, E.; Groen, J.; Evans, B.
• Other Names: Rontogiannis Athanasios Academic Editor.
• Is Part Of: EURASIP journal on advances in signal processing. Volume 2009(2009)
• Publication Date: 2009-04-06
• Subjects: Signal processing -- Periodicals; Traitement du signal; Signal processing; Periodicals; 621.3822
• DOI: 10.1155/2009/109438
• Languages: English
• ISSNs: 1687-6172

Abstract

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.