Browse > Article
http://dx.doi.org/10.9708/jksci.2012.17.2.049

An Enhanced Spatial Fuzzy C-Means Algorithm for Image Segmentation  

Truong, Tung X. (School of Electrical Engineering, University of Ulsan)
Kim, Jong-Myon (School of Electrical Engineering, University of Ulsan)
Publication Information
Journal of the Korea Society of Computer and Information / v.17, no.2, 2012 , pp. 49-57 More about this Journal
Abstract
Conventional fuzzy c-means (FCM) algorithms have achieved a good clustering performance. However, they do not fully utilize the spatial information in the image and this results in lower clustering performance for images that have low contrast, vague boundaries, and noises. To overcome this issue, we propose an enhanced spatial fuzzy c-means (ESFCM) algorithm that takes into account the influence of neighboring pixels on the center pixel by assigning weights to the neighbors in a $3{\times}3$ square window. To evaluate between the proposed ESFCM and various FCM based segmentation algorithms, we utilized clustering validity functions such as partition coefficient ($V_{pc}$), partition entropy ($V_{pe}$), and Xie-Bdni function ($V_{xb}$). Experimental results show that the proposed ESFCM outperforms other FCM based algorithms in terms of clustering validity functions.
Keywords
fuzzy c-means algorithm; image segmentation; membership function; clustering validity functions;
Citations & Related Records
연도 인용수 순위
  • Reference
1 J. C. Bezdek, "Mathematical Models for Systematic and Taxonomy," in Proc. Int'l Conf. Numerical Taxonomy, pp. 143-166, 1975.
2 X. L. Xei, G. A. Beni, "Validity Measure for Fuzzy Clustering," IEEE Trans. Pattern Analysis and Machine Intelligence, Vol. 3, pp. 841-846, Aug. 1991.
3 W. Cai, S. Chen, D. Zhang, "Fast and Robust Fuzzy C-Means Clustering Algorithms Incorporating Local Information for Image Segmentation," Pattern Recognition, Vol. 40, No. 3, pp. 825-838, March 2007.   DOI   ScienceOn
4 D. L. Pham, "Fuzzy Clustering with Spatial Constraints," in Proc. Int'l Conf. Image Proc., Vol. 2, pp. 65-68, Hong Kong, Dec. 2002.
5 S. R. Kannan, S. Ramathilagam, P. Pandiyarajan, A. Sathya, "Fuzzy Clustering Approach in Segmen tation of T1-T2 Brain MRI," Int'l J. Recent Trends in Eng., Vol. 2, No. 1, pp. 157-160, Nov. 2009.
6 K. S. Chuang, H. L. Tzeng, S. Chen, J. Wu, T. J. Chen, "Fuzzy C-Means Clustering with Spatial Information for Image Segmentation," Computerize d Medical Imaging and Graphics, Vol. 30, No. 1, pp. 9-15, Jan. 2006.   DOI   ScienceOn
7 S. Krinidis, V. Chatzis, "A Robust Fuzzy Local Information C-Means Clustering Algorithm," IEEE Trans. Image Proc., Vol, 19, No. 5, pp. 1328-1337, Jan. 2010.   DOI   ScienceOn
8 A. W. C. Liew, S. H. Leung, W. H. Lau, "Fuzzy Image Clustering Incorporating Spatial Continuity," IEE Proc. Vision, Image and Signal Proc., Vol. 147, No. 2, pp. 185-192, April 2000.   DOI   ScienceOn
9 N. A. Mohamed, M. N. Ahmed, A. Farag, "Modified Fuzzy C-Mean in Medical Image Segmentation," in Proc. IEEE Int'l Conf. Acoust., Speech, and Signal Proc., Vol. 6, pp. 3429-3432, March 1999.
10 S. Z. Beevi, M. M. Sathik, "A Robust Segmentation Approach for Noisy Medical Images Using Fuzzy Clustering with Spatial Probability," European J. Scientific Research, Vol. 41, No. 3, pp. 437-451, 2010.
11 N. R. Pal, J. C. Bezdek, "On Cluster Validity for the Fuzzy C-Means Model," IEEE Trans. Fuzzy System, Vol. 3, pp. 370-379, Aug. 1995.   DOI   ScienceOn
12 J. C. Bezdek, "Cluster Validity with Fuzzy Sets," J. Cybernetics and Syst., Vol. 3, pp. 58-73, 1973.   DOI
13 J. C. Bezdek, J. Keller, R. Krisnapuram, N. Pal, "Fuzzy Models and Algorithms for Pattern Recogn ition and Image Processing," Kluwer Academ ic, Norwell, 2005.
14 N. R. Pal, S. K. Pal, "A Review on Image Segmentation Techniques," Patter Recognition, Vol. 26, No. 9, pp. 1277-1294, Sept. 1993.   DOI   ScienceOn
15 K. S. Fu, J. K. Mu, "A Survey on Image Segmentation," Pattern Segmentation, Vol. 13, No. 1, pp. 3-16, 1981.
16 J. C. Bezdek, "Pattern Recognition with Fuzzy Objective Function Algorithms," Pleum Press, New York, 1981.
17 S. Naz, H. Majeed, H. Irshad, "Image Segmentation Using Fuzzy Clustering: A Survey," in Proc. IEEE Int'l Conf. Emerging Technologies, pp. 181-186, Nov. 2010.
18 L. Szilagyi, Z. Benyo, S. M. Szilagyi, H. S. Adam, "MR Brain Image Segmentation Using an Enhanced Fuzzy C-Means Algorithm," in Proc. IEEE Int'l Conf. Eng. in Medicine and Biology Soc., Vol. 1, pp. 724-726, April 2003.
19 S. Chen, D. Zhang, "Robust Image Segmentation Using FCM with Spatial Constraints Based on New Kernel-Induced Distance Measure," IEEE Trans. Syst., Man, and Cybernetics-Part B: Cybernetics, Vol. 34, No. 4, pp. 1907-1916, July 2004.   DOI   ScienceOn