Mdakane, Lizwe WKleynhans, Waldo2018-01-312018-01-312017-06Mdakane, L.W. and Kleynhans, W. 2017. An image-segmentation-based framework to detect oil slicks from moving vessels in the Southern African oceans using SAR imagery. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 10(6): 2810-28181939-1404http://ieeexplore.ieee.org/document/7874093/DOI: 10.1109/JSTARS.2017.2671403http://hdl.handle.net/10204/10000Copyright: 2017 IEEE. Due to copyright restrictions, the attached PDF file only contains the abstract of the full text item. For access to the full text item, please consult the publisher's website.Oil slick events caused due to bilge leakage/dumps from ships and from other anthropogenic sources pose a threat to the aquatic ecosystem and need to be monitored on a regular basis. An automatic image-segmentation-based framework to detect oil slick from moving vessels using spaceborne synthetic aperture radar (SAR) images over Southern African oceans was proposed. The study uses an automated threshold-based algorithm and a region-based algorithm to achieve a more efficient oil slick detection. The proposed framework consisted of two parts: First, a threshold-based method was used to detect areas with a high oil slick probability; second, a region-based method was used to extract the full extent of the detected oil slick. The proposed framework was tested on both real SAR and synthetic SAR images and was robust to intensity variations, weak boundaries, and was also more computationally efficient when compared to the region-based method without the threshold-based input.enActive contoursmodelLevel setBilge waste dumpingOil spillsSegmentationSynthetic aperture radarSARArticleMdakane, L. W., & Kleynhans, W. (2017). An image-segmentation-based framework to detect oil slicks from moving vessels in the Southern African oceans using SAR imagery. http://hdl.handle.net/10204/10000Mdakane, Lizwe W, and Waldo Kleynhans "An image-segmentation-based framework to detect oil slicks from moving vessels in the Southern African oceans using SAR imagery." (2017) http://hdl.handle.net/10204/10000Mdakane LW, Kleynhans W. An image-segmentation-based framework to detect oil slicks from moving vessels in the Southern African oceans using SAR imagery. 2017; http://hdl.handle.net/10204/10000.TY - Article AU - Mdakane, Lizwe W AU - Kleynhans, Waldo AB - Oil slick events caused due to bilge leakage/dumps from ships and from other anthropogenic sources pose a threat to the aquatic ecosystem and need to be monitored on a regular basis. An automatic image-segmentation-based framework to detect oil slick from moving vessels using spaceborne synthetic aperture radar (SAR) images over Southern African oceans was proposed. The study uses an automated threshold-based algorithm and a region-based algorithm to achieve a more efficient oil slick detection. The proposed framework consisted of two parts: First, a threshold-based method was used to detect areas with a high oil slick probability; second, a region-based method was used to extract the full extent of the detected oil slick. The proposed framework was tested on both real SAR and synthetic SAR images and was robust to intensity variations, weak boundaries, and was also more computationally efficient when compared to the region-based method without the threshold-based input. DA - 2017-06 DB - ResearchSpace DP - CSIR KW - Active contoursmodel KW - Level set KW - Bilge waste dumping KW - Oil spills KW - Segmentation KW - Synthetic aperture radar KW - SAR LK - https://researchspace.csir.co.za PY - 2017 SM - 1939-1404 T1 - An image-segmentation-based framework to detect oil slicks from moving vessels in the Southern African oceans using SAR imagery TI - An image-segmentation-based framework to detect oil slicks from moving vessels in the Southern African oceans using SAR imagery UR - http://hdl.handle.net/10204/10000 ER -