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Proceedings Paper

Comparison of prescreening algorithms for target detection in synthetic aperture sonar imagery
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Paper Abstract

Automated anomaly and target detection are commonly used as a prescreening step within a larger target detection and target classification framework to find regions of interest for further analysis. A number of anomaly and target detection algorithms have been developed in the literature for application to target detection in Synthetic Aperture Sonar (SAS) imagery. In this paper, a comparison of two anomaly and one target detection algorithm for target detection in synthetic aperture sonar is presented. In the comparison, each method is tested on a large set of real sonar imagery and results are evaluated using receiver operating characteristic curves. The results are compiled and quantitatively shown to highlight the strengths and weakness of the variety of approaches within various sea-floor environments and on particular target shapes and types.

Paper Details

Date Published: 30 April 2018
PDF: 8 pages
Proc. SPIE 10628, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXIII, 1062811 (30 April 2018); doi: 10.1117/12.2305175
Show Author Affiliations
Princess Lyons, Univ. of Florida (United States)
Daniel Suen, Univ. of Florida (United States)
Aquila Galusha, Univ. of Missouri (United States)
Alina Zare, Univ. of Florida (United States)
James Keller, Univ. of Missouri (United States)


Published in SPIE Proceedings Vol. 10628:
Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXIII
Steven S. Bishop; Jason C. Isaacs, Editor(s)

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