Paper
21 October 2005 A decision support system for ship identification based on the curvature scale space representation
Author Affiliations +
Proceedings Volume 5988, Electro-Optical Remote Sensing; 59880K (2005) https://doi.org/10.1117/12.630532
Event: European Symposium on Optics and Photonics for Defence and Security, 2005, Bruges, Belgium
Abstract
In this paper, a decision support system for ship identification is presented. The system receives as input a silhouette of the vessel to be identified, previously extracted from a side view of the object. This view could have been acquired with imaging sensors operating at different spectral ranges (CCD, FLIR, image intensifier). The input silhouette is preprocessed and compared to those stored in a database, retrieving a small number of potential matches ranked by their similarity to the target silhouette. This set of potential matches is presented to the system operator, who makes the final ship identification. This system makes use of an evolved version of the Curvature Scale Space (CSS) representation. In the proposed approach, it is curvature extrema, instead of zero crossings, that are tracked during silhouette evolution, hence improving robustness and enabling to cope successfully with cases where the standard CCS representation is found to be unstable. Also, the use of local curvature was replaced with the more robust concept of lobe concavity, with significant additional gains in performance. Experimental results on actual operational imagery prove the excellent performance and robustness of the developed method.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Álvaro Enríquez de Luna, Carlos Miravet, Deitze Otaduy, and Carlos Dorronsoro "A decision support system for ship identification based on the curvature scale space representation", Proc. SPIE 5988, Electro-Optical Remote Sensing, 59880K (21 October 2005); https://doi.org/10.1117/12.630532
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Cited by 8 scholarly publications.
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KEYWORDS
Databases

Visualization

Image processing

Image sensors

Decision support systems

Image filtering

System identification

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