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


Schwegmann, CP and Kleynhans, W and Salmon, BP, Ship detection in South African oceans using a SAR, CFAR and a Haar-like feature classifier, Proceedings of the International Geoscience and Remote Sensing Symposium (IGARSS), 13-18 July 2014, Quebec, Canada, pp. 557-560. ISBN 978-147995775-0 (2014) [Refereed Conference Paper]

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Copyright Statement

Copyright 2014 the Authors

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DOI: doi:10.1109/IGARSS.2014.6946483


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 prescreening 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.

Item Details

Item Type:Refereed Conference Paper
Keywords:Synthetic Aperture Radar, Constant False Alarm Rate, Haar-like features
Research Division:Engineering
Research Group:Communications engineering
Research Field:Signal processing
Objective Division:Expanding Knowledge
Objective Group:Expanding knowledge
Objective Field:Expanding knowledge in engineering
UTAS Author:Salmon, BP (Dr Brian Salmon)
ID Code:92403
Year Published:2014
Web of Science® Times Cited:5
Deposited By:Engineering
Deposited On:2014-06-17
Last Modified:2018-04-05

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