Adaptive Fusion Architecture for Context Aware Detection and Classification

Author

Bell, J. ; Petillot, Y. ; Lebart, K. ; Mignotte, P.Y. ; Coiras, E. ; Rohou, H.

Author_Institution

Heriot-Watt Univ., Edinburgh

fYear

2007

fDate

18-21 June 2007

Firstpage

1

Lastpage

6

Abstract

This paper presents a framework for the fusion of detection and classification algorithms for side-scan imagery. The framework is based on Dempster-Shafer theory of evidence, which permits the fusion of heterogeneous outputs of targets detectors and classifiers. The paper will illustrate how the technique permits the incorporation of contextual information into the decision process, giving more importance to the outputs of those algorithms that perform better in particular mission conditions.

Keywords

adaptive signal processing; geophysical signal processing; image classification; object detection; oceanographic techniques; sensor fusion; sonar detection; sonar imaging; sonar target recognition; Dempster-Shafer theory of evidence; adaptive fusion architecture; context aware classification; context aware detection; side-scan imagery; sonar detection; target classification; Classification algorithms; Context awareness; Data mining; Detectors; Feature extraction; Object detection; Sonar detection; Underwater tracking; Underwater vehicles; Vehicle detection; classification; detection; fusion; sonar;

fLanguage

English

Publisher

ieee

Conference_Titel

OCEANS 2007 - Europe

Conference_Location

Aberdeen

Print_ISBN

978-1-4244-0635-7

Electronic_ISBN

978-1-4244-0635-7

Type

conf

DOI

10.1109/OCEANSE.2007.4302247

Filename

4302247