International Journal of Image, Graphics and Signal Processing(IJIGSP)

ISSN: 2074-9074 (Print), ISSN: 2074-9082 (Online)

Published By: MECS Press

IJIGSP Vol.4, No.6, Jul. 2012

A Hybrid Approach for Image Segmentation Using Fuzzy Clustering and Level Set Method

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Sanjay Kumar,Santosh Kumar Ray,Peeyush Tewari

Index Terms

Image Segmentation, Fuzzy c-means, Level set method


Image segmentation is a growing field and it has been successfully applied in various fields such as medical imaging, face recognition, etc. In this paper, we propose a method for image segmentation that combines a region based artificial intelligence technique named fuzzy c-means (FCM) and a boundary based mathematical modeling technique level set method (LSM). In the proposed method, the contour of the image is obtained by FCM method which serves as initial contour for LSM Method. The final segmentation is achieved using LSM which uses signed pressure force (spf) function for active control of contour.

Cite This Paper

Sanjay Kumar,Santosh Kumar Ray,Peeyush Tewari,"A Hybrid Approach for Image Segmentation Using Fuzzy Clustering and Level Set Method", IJIGSP, vol.4, no.6, pp.1-7, 2012.


[1]D. L. Pham, C. Xu, and J. L. Prince, “A Survey of Current Methods in Medical Image Segmenatation”, Annual Review of Biomedical Engineering, Vol. 2, 2000, pp. 315-338.

[2]N. Sharma and L. M. Aggarwal, “Automated Medical Image Segmentation Techniques”, Journal of Medical Physics, 2010, pp. 3-14.

[3]T. Zuva, et al., “Image Segmentation, Available Techniques, Developments and Open Issues”, Canadian Journal of Image Processing and Computer Vision, Vol. 2, No. 3, 2011, pp. 20-29.

[4]V. Caselles, et al., “Geodesic Active Contours”, International Journal of Computer Vision, Vol. 22, No. 1, 1997, pp. 61-79.

[5]S. Osher, J. A. Sethian, “Fronts Propagating with Curvature Dependent Speed: Algorithms Based on Hamilton-Jacobi Formulations”, Journal of Computational Physics, Vol 79, 1988, pp. 12-49.

[6]J. C. Dunn, “A Fuzzy Relative of the ISODATA Process and Its Use in Detecting Compact Well-Separated Clusters”, Journal of Cybernetics, Vol. 3, No. 3, 1973, pp. 32-57.

[7]J. C. Bezdek, Pattern Recognition with Fuzzy Objective Function Algorithms, Plenum Press, 1981.

[8]N. A. Mohamed, et al., “Modified Fuzzy C-Mean in Medical Image Segmentation”, Proceedings of the Acoustics, Speech, and Signal Processing, 1999. On 1999 IEEE International Conference, 1999, pp. 3429-3432.

[9]L. Szilagyi, et al., “A Modified Fuzzy C-Means Algorithm for MR Brain Image Segmentation”, Image Analysis and Recognition, 2007, pp. 866-877.

[10]K. H. Yuan, et al., “A Novel Fuzzy C-Means Algorithm and Its Application”, International Journal of Pattern Recoginition and Artificial Intelligence, Vol. 19, No. 8, 2005, pp. 1059-1066.

[11]Q. Zhao, et al., “Improved Fuzzy C-Means Segmentation Algorithm for Images with Intensity Inhomogeneity”, Analysis and Design of Intelligent Systems Using Soft Computing Techniques, 2007, pp, 150-159. 

[12]J. Kang, et al., “Fingerprint Image Segmentation Using Modified Fuzzy C-Means Algorithm”, Journal of Biomedical Science and Engineering, Vol. 2, 2009, pp. 656-660.

[13]B. Li, et al., “Integrating Spatial Fuzzy Clustering with Level Set Methods for Automated Medical Image Segmentation”, Computers in Biology and Medicine, Elsevier, Vol. 41, No. 1, 2011, pp. 1-10.

[14]K.S. Chuang, et al., ”Fuzzy C Means Clustering with Spatial Information for Image Segmentation”, Computerized Medical Imaging and Graphics, Elsevier, Vol. 30, No. 1, 2006, pp. 9-15.

[15]W. Cai, et al., “Fast and Robust Fuzzy C-Means Clustering Algorithms Incorporating Local Information for Image Segmentation”, Pattern Recogination, Vol. 40, No. 3, 2007, pp. 825-838.

[16]K. Zhang, et al., “Active Contours with Selective Local or Global Segmentation: A New Formulation and Level Set Method”, Image and Vision Computing, Vol. 28, No. 4, Elsevier B. V., 2010, pp. 668-676.

[17]T.F. Chan, L.A. Vese, “Active Contours Without Edges”, IEEE Transactions on Image Processing, Vol. 10, No. 2, 2001, pp. 266-277. 

[18]C. Y. Xu, “On The Relationship Between Parametric and Geometric Active Contours”, Processing of 34th Asilomar Conference on Signals Systems and Computers, IEEE, Vol. 1, Issue: October, 2000, pp. 483-489.

[19]G. Zhu, et al., “Boundary-Based Image Segmentation Using Binary Level Set Method”, Optical Engineering, Vol. 46, No. 5, 2007, pp. 050501-1-3.

[20]C. Li, et al., “Level Set Evolution Without Re-Initialization: A New Variational Formulation”, Proceedings of the 2005 IEEE Conference on Computer Society Conference on Computer Vision and Pattern Recoginition (CVPR’05), 2005, pp. 430-436.

[21]Z. Chi, et al., “Fuzzy Algorithms: With Applications to Image Procesing and Pattern Recognition”, World Scientific Publishing Co. Pte. Ltd., 1996, pp. 88.

[22]J. A. Sethian, “Level Set Methods and Fast Marching Methods”, Cambridge University Press, Cambridge UK, 1999, pp. 6-7.