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Authors: Wafa Moualhi and Ezzeddine Zagrouba

Affiliation: Team research SIIVA, Tunisia

Keyword(s): Fuzzy-c-means clustering (FCM), Image segmentation, MR imaging, Spatial information.

Related Ontology Subjects/Areas/Topics: Applications ; Computer Vision, Visualization and Computer Graphics ; Image and Video Coding and Compression ; Image Enhancement and Restoration ; Image Formation and Preprocessing ; Medical Imaging ; Pattern Recognition ; Software Engineering

Abstract: Fuzzy-c-means (FCM) algorithm is widely used for magnetic resonance (MR) image segmentation. However, conventional FCM is sensitive to noise because it does not consider the spatial information in the image. To overcome the above problem, an FCM algorithm with spatial information is presented in this paper. The algorithm is realized by integrating spatial contextual information into the membership function to make the method less sensitive to noise. The new spatial information term is defined as the summation of the membership function in the neighborhood of pixel under consideration weighted by a parameter  to control the neighborhood effect. This new method is applied to both synthetic images and MR data. Experimental results show that the presented method is more robust to noise than the conventional FCM and yields homogenous labeling.

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Paper citation in several formats:
Moualhi, W. and Zagrouba, E. (2009). ROBUST FUZZY-C-MEANS FOR IMAGE SEGMENTATION. In Proceedings of the First International Conference on Computer Imaging Theory and Applications (VISIGRAPP 2009) - IMAGAPP; ISBN 978-989-8111-68-5, SciTePress, pages 87-91. DOI: 10.5220/0001787000870091

@conference{imagapp09,
author={Wafa Moualhi. and Ezzeddine Zagrouba.},
title={ROBUST FUZZY-C-MEANS FOR IMAGE SEGMENTATION},
booktitle={Proceedings of the First International Conference on Computer Imaging Theory and Applications (VISIGRAPP 2009) - IMAGAPP},
year={2009},
pages={87-91},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001787000870091},
isbn={978-989-8111-68-5},
}

TY - CONF

JO - Proceedings of the First International Conference on Computer Imaging Theory and Applications (VISIGRAPP 2009) - IMAGAPP
TI - ROBUST FUZZY-C-MEANS FOR IMAGE SEGMENTATION
SN - 978-989-8111-68-5
AU - Moualhi, W.
AU - Zagrouba, E.
PY - 2009
SP - 87
EP - 91
DO - 10.5220/0001787000870091
PB - SciTePress

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