Paper
1 May 2007 Automated detection of objects in sidescan sonar data
John M. Irvine, Steven A. Israel, Stuart M. Bergeron
Author Affiliations +
Abstract
Detection and mapping of subsurface obstacles is critical for safe navigation of littoral regions. Sidescan sonar data offers a rich source of information for developing such maps. Typically, data are collected at two frequencies using a sensor mounted on a towfish. The major features of interest depend on the specific mission, but often include: objects on the bottom that could pose hazards for navigation, linear features such as cables or pipelines, and the bottom type, e.g., clay, sand, rock, etc. A number of phenomena can complicate the analysis of the sonar data: Surface return, vessel wakes, fluctuations in the position and orientation of the towfish. Developing accurate maps of navigation hazards based on sidescan sonar data is generally labor intensive. We propose an automated approach, which employs commercial software tools, to detect of these objects. This method offers the prospect of substantially reducing production time for maritime geospatial data products.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
John M. Irvine, Steven A. Israel, and Stuart M. Bergeron "Automated detection of objects in sidescan sonar data", Proc. SPIE 6578, Defense Transformation and Net-Centric Systems 2007, 65781K (1 May 2007); https://doi.org/10.1117/12.724945
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KEYWORDS
Image segmentation

Image processing

Sensors

Image classification

Acoustics

Associative arrays

Image analysis

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