Abstract
This paper presents a fuzzy clustering algorithm, called an alternative fuzzy compactness & separation (AFCS) algorithm that is based on an exponential-type distance function. The proposed AFCS algorithm is more robust than the fuzzy c-means (FCM) and the fuzzy compactness & separation (FCS) proposed by Wu et al. (2005). Some numerical experiments are performed to assess the performance of FCM, FCS and AFCS algorithms. Numerical results show that the AFCS has better performance than the FCM and FCS from the robust point of view.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Baraldi, A., Blonda, P.: A survey of fuzzy clustering algorithms for pattern recognition part I and II. IEEE Trans. Systems, Man and Cybernetics-part B 29, 778–801 (1999)
Bezdek, J.C.: Pattern Recognition with Fuzzy Objective Function Algorithms. Plenum Press, New York (1981)
Duda, R.O., Hart, P.E.: Pattern Classification and Scene Analysis. Wiley, New York (1973)
Gath, J., Geva, A.B.: Unsupervised optimal fuzzy clustering. IEEE Trans. Pattern Anal. Mach. Intell. 11, 773–781 (1989)
Gustafson, D.E., Kessel, W.C.: Fuzzy clustering with a fuzzy covariance matrix. In: Proc. IEEE Conf. Decision Contr., San Diego, CA, pp. 761–776 (1979)
Hathaway, R.J., Bezdek, J.C., Hu, Y.: Generalized fuzzy c-means clustering strategies using Lp norm distances. IEEE Trans. Fuzzy Systems 8, 576–582 (2000)
Hoppner, F., Klawonn, F., Kruse, R., Runkler, T.: Fuzzy Cluster Analysis: Methods for Classification Data Analysis and Image Recognition. Wiley, New York (1999)
Krishnapuram, R., Kim, J.: Clustering algorithms based on volume criteria. IEEE Trans. Fuzzy Syst. 8, 228–236 (2000)
Özdemir, D., Akarun, L.: A fuzzy algorithm for color quantization of images. Pattern Recognition 35, 1785–1791 (2002)
Wu, K.L., Yang, M.S.: Alternative c-means clustering algorithms. Pattern Recognition 35, 2267–2278 (2002)
Wu, K.L., Yu, J., Yang, M.S.: A novel fuzzy clustering algorithm based on a fuzzy scatter matrix with optimality tests. Pattern Recognition Letters 26, 639–652 (2005)
Yang, M.S.: A survey of fuzzy clustering. Mathematical and Computer Modeling 18(11), 1–16 (1993)
Yu, J., Yang, M.S.: Optimality test for generalized FCM and its application to parameter selection. IEEE Trans. Fuzzy Systems 13, 164–176 (2005)
Zadeh, L.A.: Fuzzy sets. Information and Control 8, 338–353 (1965)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Yang, MS., Tsai, HS. (2005). An Alternative Fuzzy Compactness and Separation Clustering Algorithm. In: Blanc-Talon, J., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2005. Lecture Notes in Computer Science, vol 3708. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11558484_19
Download citation
DOI: https://doi.org/10.1007/11558484_19
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29032-2
Online ISBN: 978-3-540-32046-3
eBook Packages: Computer ScienceComputer Science (R0)