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Proceedings Paper

Integrated fuzzy classification system for automatic oil spill detection using SAR images
Author(s): Iphigenia Keramitsoglou; Constantinos Cartalis; Chris T. Kiranoudis
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Paper Abstract

Synthetic Aperture Radar (SAR) images are extensively used for the determination of oil slicks in the marine environment, as they are independent of local weather conditions and cloudiness. Oil spills are recognized by the expert's eye as dark patterns of characteristic shape in particular context. However, the major difficulty to be dealt with is to differentiate between oil spills and look-alikes of natural origin. A fully automated system for the identification of possible oil spills that imitates the expert's choice and decisions has been developed. The system's architecture comprises several distinct modules of supplementary operation (georeferencing, land masking, thresholding, segmentation) and uses their contribution to the analysis and assignment of the probability of a dark image shape to be an oil spill by means of a fuzzy classifier. The output consists of several images and table providing the user with all relevant information as well as supporting decision making. The case study area was the Aegean Sea in Greece. The system responded very satisfactorily for all 35 images processed. The complete procedure described is a fully automated stand-alone application running under Windows operating system.

Paper Details

Date Published: 7 March 2003
PDF: 10 pages
Proc. SPIE 4883, SAR Image Analysis, Modeling, and Techniques V, (7 March 2003); doi: 10.1117/12.463184
Show Author Affiliations
Iphigenia Keramitsoglou, Univ. of Athens (Greece)
Constantinos Cartalis, Univ. of Athens (Greece)
Chris T. Kiranoudis, National Technical Univ. of Athens (Greece)


Published in SPIE Proceedings Vol. 4883:
SAR Image Analysis, Modeling, and Techniques V
Francesco Posa, Editor(s)

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