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Computational Ecology and Software, 2014, 4(2): 129-134
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Article

Synthetic Aperture Radar (SAR) image segmentation by fuzzy c-means clustering technique with thresholding for iceberg images

Usman Seljuq1, Rashid Hussain2
1Sir Syed University of Engineering and Technology Karachi-75300, Pakistan
2Faculty of Engineering Science and Technology, Hamdard University, Karachi 74600, Pakistan

Received 27 December 2013;Accepted 5 February 2014;Published online 1 June 2014
IAEES

Abstract
Fuzzy c-means (FCM) clustering algorithm is widely used for image segmentation. The purpose of clustering is to identify natural groupings of data from a large data set, which results in concise representation of system's behavior. It can be used to detect icebergs regardless of ambient conditions like rain, darkness and fog. As a result SAR images can be used for iceberg surveillance. In this paper we have investigate FCM with thresholding for iceberg image segmentation for Synthetic Aperture Radar (SAR) images. The results showed that the assessment parameters; mean and entropy have lower values for efficient segmentation.

Keywords Synthetic Aperture Radar (SAR);fuzzy c-means clustering;thresholding;image segmentation.


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