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Proceedings Paper

Application of fusion algorithms for computer aided detection and classification of bottom mines to synthetic aperture sonar test data
Author(s): Charles M. Ciany; William C. Zurawski
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Paper Abstract

Over the past several years, Raytheon Company has adapted its Computer Aided Detection/Computer-Aided Classification (CAD/CAC) algorithm to process side-scan sonar imagery taken in both the Very Shallow Water (VSW) and Shallow Water (SW) operating environments. This paper describes the further adaptation of this CAD/CAC algorithm to process Synthetic Aperture Sonar (SAS) image data taken by an Autonomous Underwater Vehicle (AUV). The tuning of the CAD/CAC algorithm for the vehicle's sonar is described, the resulting classifier performance is presented, and the fusion of the classifier outputs with those of another CAD/CAC processor is evaluated. The fusion algorithm accepts the classification confidence levels and associated contact locations from the different CAD/CAC algorithms, clusters the contacts based on the distance between their locations, and then declares a valid target when a clustered contact passes a prescribed fusion criterion. Three different fusion criteria are evaluated: the first based on thresholding the sum of the confidence factors for the clustered contacts, the second based on simple binary combinations of the multiple CAD/CAC processor outputs, and the third based on the Fisher Discriminant. The resulting performance of the three fusion algorithms is compared, and the overall performance benefit of a significant reduction of false alarms at high correct classification probabilities is quantified.

Paper Details

Date Published: 18 May 2006
PDF: 8 pages
Proc. SPIE 6217, Detection and Remediation Technologies for Mines and Minelike Targets XI, 62171D (18 May 2006); doi: 10.1117/12.666100
Show Author Affiliations
Charles M. Ciany, Raytheon Integrated Defense Systems (United States)
William C. Zurawski, Raytheon Integrated Defense Systems (United States)


Published in SPIE Proceedings Vol. 6217:
Detection and Remediation Technologies for Mines and Minelike Targets XI
J. Thomas Broach; Russell S. Harmon; John H. Holloway Jr., Editor(s)

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