Sonar image interpretation and modelling

George T. Russell, Judith M. Bell, Patrik O B Holt, Stuart J. Clarke

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The problem addressed is that of providing a model-based system to interpret sonar data from an autonomous or remotely controlled vehicle instrumentation, to aid navigation, improve sea floor mapping techniques, identify objects, simulate acoustic images for survey and analysis, or to aid the design of sonar systems. Analytic tools have been developed to segment and classify seabed and shallow seismic image textures, remove multiple reflections and detect objects on or close to the seabed. These have been used to provide an efficient data compression scheme for sonar images to increase the transmission rate of images over an acoustic communications link. The sonar interpretation problem is placed within a model-based framework. This paper presents the conceptual sonar simulation system architecture, outlines the visualisation of the three dimensional sea floor model, describes the sonar system simulation and references image analysis tools available for texture segmentation and object detection.

Original languageEnglish
Title of host publicationProceedings of the IEEE Symposium on Autonomous Underwater Vehicle Technology
Pages317-324
Number of pages8
Publication statusPublished - 1996
Event1996 IEEE Symposium on Autonomous Underwater Vehicle Technology - Monterey, CA, USA
Duration: 2 Jun 19966 Jun 1996

Conference

Conference1996 IEEE Symposium on Autonomous Underwater Vehicle Technology
CityMonterey, CA, USA
Period2/06/966/06/96

Fingerprint

Sonar
Acoustics
Image texture
Bridge decks
Data compression
Image analysis
Telecommunication links
Navigation
Visualization
Textures

Cite this

Russell, G. T., Bell, J. M., Holt, P. O. B., & Clarke, S. J. (1996). Sonar image interpretation and modelling. In Proceedings of the IEEE Symposium on Autonomous Underwater Vehicle Technology (pp. 317-324)
Russell, George T. ; Bell, Judith M. ; Holt, Patrik O B ; Clarke, Stuart J. / Sonar image interpretation and modelling. Proceedings of the IEEE Symposium on Autonomous Underwater Vehicle Technology. 1996. pp. 317-324
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Russell, GT, Bell, JM, Holt, POB & Clarke, SJ 1996, Sonar image interpretation and modelling. in Proceedings of the IEEE Symposium on Autonomous Underwater Vehicle Technology. pp. 317-324, 1996 IEEE Symposium on Autonomous Underwater Vehicle Technology, Monterey, CA, USA, 2/06/96.

Sonar image interpretation and modelling. / Russell, George T.; Bell, Judith M.; Holt, Patrik O B; Clarke, Stuart J.

Proceedings of the IEEE Symposium on Autonomous Underwater Vehicle Technology. 1996. p. 317-324.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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AU - Holt, Patrik O B

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N2 - The problem addressed is that of providing a model-based system to interpret sonar data from an autonomous or remotely controlled vehicle instrumentation, to aid navigation, improve sea floor mapping techniques, identify objects, simulate acoustic images for survey and analysis, or to aid the design of sonar systems. Analytic tools have been developed to segment and classify seabed and shallow seismic image textures, remove multiple reflections and detect objects on or close to the seabed. These have been used to provide an efficient data compression scheme for sonar images to increase the transmission rate of images over an acoustic communications link. The sonar interpretation problem is placed within a model-based framework. This paper presents the conceptual sonar simulation system architecture, outlines the visualisation of the three dimensional sea floor model, describes the sonar system simulation and references image analysis tools available for texture segmentation and object detection.

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M3 - Conference contribution

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BT - Proceedings of the IEEE Symposium on Autonomous Underwater Vehicle Technology

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Russell GT, Bell JM, Holt POB, Clarke SJ. Sonar image interpretation and modelling. In Proceedings of the IEEE Symposium on Autonomous Underwater Vehicle Technology. 1996. p. 317-324