Automatic Target Recognition in Synthetic Aperture Sonar Images Based on Geometrical Feature Extraction
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 object...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2009-01-01
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| Series: | EURASIP Journal on Advances in Signal Processing |
| Online Access: | http://dx.doi.org/10.1155/2009/109438 |
| _version_ | 1818236891457126400 |
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| author | J. Del Rio Vera E. Coiras J. Groen B. Evans |
| author_facet | J. Del Rio Vera E. Coiras J. Groen B. Evans |
| author_sort | J. Del Rio Vera |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-12T12:17:04Z |
| format | Article |
| id | doaj.art-03d386088c9240ebb19a600f02f85d9d |
| institution | Directory Open Access Journal |
| issn | 1687-6172 1687-6180 |
| language | English |
| last_indexed | 2024-12-12T12:17:04Z |
| publishDate | 2009-01-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | EURASIP Journal on Advances in Signal Processing |
| spelling | doaj.art-03d386088c9240ebb19a600f02f85d9d2022-12-22T00:24:44ZengSpringerOpenEURASIP Journal on Advances in Signal Processing1687-61721687-61802009-01-01200910.1155/2009/109438Automatic Target Recognition in Synthetic Aperture Sonar Images Based on Geometrical Feature ExtractionJ. Del Rio VeraE. CoirasJ. GroenB. EvansThis 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.http://dx.doi.org/10.1155/2009/109438 |
| spellingShingle | J. Del Rio Vera E. Coiras J. Groen B. Evans Automatic Target Recognition in Synthetic Aperture Sonar Images Based on Geometrical Feature Extraction EURASIP Journal on Advances in Signal Processing |
| title | Automatic Target Recognition in Synthetic Aperture Sonar Images Based on Geometrical Feature Extraction |
| title_full | Automatic Target Recognition in Synthetic Aperture Sonar Images Based on Geometrical Feature Extraction |
| title_fullStr | Automatic Target Recognition in Synthetic Aperture Sonar Images Based on Geometrical Feature Extraction |
| title_full_unstemmed | Automatic Target Recognition in Synthetic Aperture Sonar Images Based on Geometrical Feature Extraction |
| title_short | Automatic Target Recognition in Synthetic Aperture Sonar Images Based on Geometrical Feature Extraction |
| title_sort | automatic target recognition in synthetic aperture sonar images based on geometrical feature extraction |
| url | http://dx.doi.org/10.1155/2009/109438 |
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