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Ship detection in South African oceans using SAR, CFAR and a Haar-like feature classifier

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dc.contributor.author Schwegmann, CP
dc.contributor.author Kleynhans, W
dc.contributor.author Salmon, BP
dc.date.accessioned 2015-03-12T10:04:05Z
dc.date.available 2015-03-12T10:04:05Z
dc.date.issued 2014-07
dc.identifier.citation Schwegmann, C.P, Kleynhans, W and Salmon, B.P. 2014. Ship detection in South African oceans using SAR, CFAR and a Haar-like feature classifier. In: 2014 IEEE Internatonal Geoscience and Remote Sensing Symposium (IGARSS), Quebec Canada, 13-18 July 2014 en_US
dc.identifier.uri http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6946483
dc.identifier.uri http://hdl.handle.net/10204/7932
dc.description 2014 IEEE Internatonal Geoscience and Remote Sensing Symposium (IGARSS), Quebec Canada, 13-18 July 2014 en_US
dc.description.abstract Synthetic Aperture Radar images is a proven technology that can be used to detect ships at sea which have no active transponders (commonly referred to as dark targets). Various methods have been proposed that process SAR images to monitor these targets. In this paper, we propose a novel ship detection method for Advanced Synthetic Aperture Radar imagery that combines a Constant False Alarm Rate ship pre-screening method with a Haar-like feature cascade classifier. Experimental results indicate that this configuration provides a ship detection accuracy above 88% and half the False Alarm Rate of the traditional Constant False Alarm Rate method. en_US
dc.language.iso en en_US
dc.publisher IEEE en_US
dc.relation.ispartofseries Workflow;14166
dc.subject Synthetic Aperture Radar en_US
dc.subject Haar-like feature cascade classifier en_US
dc.subject South African coastal waters en_US
dc.title Ship detection in South African oceans using SAR, CFAR and a Haar-like feature classifier en_US
dc.type Conference Presentation en_US
dc.identifier.apacitation Schwegmann, C., Kleynhans, W., & Salmon, B. (2014). Ship detection in South African oceans using SAR, CFAR and a Haar-like feature classifier. IEEE. http://hdl.handle.net/10204/7932 en_ZA
dc.identifier.chicagocitation Schwegmann, CP, W Kleynhans, and BP Salmon. "Ship detection in South African oceans using SAR, CFAR and a Haar-like feature classifier." (2014): http://hdl.handle.net/10204/7932 en_ZA
dc.identifier.vancouvercitation Schwegmann C, Kleynhans W, Salmon B, Ship detection in South African oceans using SAR, CFAR and a Haar-like feature classifier; IEEE; 2014. http://hdl.handle.net/10204/7932 . en_ZA
dc.identifier.ris TY - Conference Presentation AU - Schwegmann, CP AU - Kleynhans, W AU - Salmon, BP AB - Synthetic Aperture Radar images is a proven technology that can be used to detect ships at sea which have no active transponders (commonly referred to as dark targets). Various methods have been proposed that process SAR images to monitor these targets. In this paper, we propose a novel ship detection method for Advanced Synthetic Aperture Radar imagery that combines a Constant False Alarm Rate ship pre-screening method with a Haar-like feature cascade classifier. Experimental results indicate that this configuration provides a ship detection accuracy above 88% and half the False Alarm Rate of the traditional Constant False Alarm Rate method. DA - 2014-07 DB - ResearchSpace DP - CSIR KW - Synthetic Aperture Radar KW - Haar-like feature cascade classifier KW - South African coastal waters LK - https://researchspace.csir.co.za PY - 2014 T1 - Ship detection in South African oceans using SAR, CFAR and a Haar-like feature classifier TI - Ship detection in South African oceans using SAR, CFAR and a Haar-like feature classifier UR - http://hdl.handle.net/10204/7932 ER - en_ZA


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