Title :
Ship detection in South African oceans using SAR, CFAR and a Haar-like feature classifier
Author :
Schwegmann, C.P. ; Kleynhans, W. ; Salmon, B.P.
Author_Institution :
Dept. of Electr., Electron. & Comput. Eng., Univ. of Pretoria, Pretoria, South Africa
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.
Keywords :
image classification; radar imaging; ships; synthetic aperture radar; CFAR; Haar-like feature cascade classifier; SAR; SAR images; South African oceans; advanced synthetic aperture radar imagery; constant false alarm rate ship prescreening method; ship detection accuracy; Accuracy; Feature extraction; Marine vehicles; Monitoring; Oceans; Sea measurements; Synthetic aperture radar;
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2014 IEEE International
Conference_Location :
Quebec City, QC
DOI :
10.1109/IGARSS.2014.6946483