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In this paper, a decision support system for ship identification ispresented. The system receives as input a silhouette of the vessel to beidentified, previously extracted from a side view of the object. This viewcould have been acquired with imaging sensors operating at different spectralranges (CCD, FLIR, image intensifier). The input silhouette is preprocessed andcompared to those stored in a database, retrieving a small number of potentialmatches ranked by their similarity to the target silhouette. This set ofpotential matches is presented to the system operator, who makes the final shipidentification. This system makes use of an evolved version of the CurvatureScale Space (CSS) representation. In the proposed approach, it is curvatureextrema, instead of zero crossings, that are tracked during silhouetteevolution, hence improving robustness and enabling to cope successfully withcases where the standard CCS representation is found to be unstable. Also, theuse of local curvature was replaced with the more robust concept of lobeconcavity, with significant additional gains in performance. Experimentalresults on actual operational imagery prove the excellent performance androbustness of the developed method.Comment: 12 pages, 18 figures, 1 table, SPIE 5988 Electro-Optical Remote  Sensing 200

A decision support system for ship identification based on the curvature scale space representation