An integrated fuzzy classification system for automatic oil spill detection using SAR images

Keramitsoglou, I; Cartalis, C; Kiranoudis, CT

dc.contributor.author	Keramitsoglou, I	en
dc.contributor.author	Cartalis, C	en
dc.contributor.author	Kiranoudis, CT	en
dc.date.accessioned	2014-03-01T02:49:12Z
dc.date.available	2014-03-01T02:49:12Z
dc.date.issued	2002	en
dc.identifier.issn	0277786X	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/34408
dc.subject	Automation	en
dc.subject	Fuzzy systems	en
dc.subject	Oil spills	en
dc.subject	Synthetic aperture data	en
dc.subject.other	Computer operating systems	en
dc.subject.other	Decision making	en
dc.subject.other	Fuzzy sets	en
dc.subject.other	Image analysis	en
dc.subject.other	Marine pollution	en
dc.subject.other	Oil spills	en
dc.subject.other	Probability	en
dc.subject.other	Synthetic aperture radar	en
dc.subject.other	Fuzzy classification system	en
dc.subject.other	Software Package Windows	en
dc.subject.other	Radar imaging	en
dc.title	An integrated fuzzy classification system for automatic oil spill detection using SAR images	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1117/12.463184	en
heal.identifier.secondary	http://dx.doi.org/10.1117/12.463184	en
heal.publicationDate	2002	en
heal.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 tables 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 above is a fully automated stand-alone application running under Windows operating system.	en
heal.journalName	Proceedings of SPIE - The International Society for Optical Engineering	en
dc.identifier.doi	10.1117/12.463184	en
dc.identifier.volume	4883	en
dc.identifier.spage	131	en
dc.identifier.epage	140	en