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.11, Oct. 2012

Integration of Clustering, Optimization and Partial Differential Equation Method for Improved Image Segmentation

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Jaskirat Kaur,Sunil Agrawal,Renu Vig

Index Terms

Fuzzy C-means (FCM); Particle Swarm Optimization (PSO); Darwinian PSO (DPSO); Fractional Order DPSO (FO-DPSO); FCM neighborhood (FCMN)


Image segmentation generally refers to the process that partitions an image into mutually exclusive regions that cover the image. Among the various image segmentation techniques, traditional image segmentation methods like edge detection, region based, watershed transformation etc. are widely used but have certain drawbacks, which cannot be used for the accurate result. In this paper clustering based techniques is employed on images which results into segmentation of images. The performance of Fuzzy C-means (FCM) integrated with the Particle Swarm optimization (PSO) technique and its variations are analyzed in different application fields. To analyze and grade the performance, computational and time complexity of techniques in different fields several metrics are used namely global consistency error, probabilistic rand index and variation of information are used. This experimental performance analysis shows that FCM along with fractional order Darwinian PSO give better performance in terms of classification accuracy, as compared to other variation of other techniques used. The integrated algorithm tested on images proves to give better results visually as well as objectively. Finally, it is concluded that fractional order Darwinian PSO along with neighborhood Fuzzy C-means and partial differential equation based level set method is an effective image segmentation technique to study the intricate contours provided the time complexity should be as small as possible to make it more real time compatible.

Cite This Paper

Jaskirat Kaur,Sunil Agrawal,Renu Vig,"Integration of Clustering, Optimization and Partial Differential Equation Method for Improved Image Segmentation", IJIGSP, vol.4, no.11, pp.26-33, 2012.


[1]Gonzalez, Woods, and Eddins, Digital Image Processing Using MATLAB, Prentice Hall 2004.

[2]A.K. Jain, M.N. Murty, P.J. Flynn, Data Clustering: A Review, ACM Computing Surveys, Vol. 31, No. 3, September 1999.

[3]Hui Zhang, Improved Clustering-Based Image Segmentation through Learning, A Dissertation, Department of Computer Science and Engineering, August 2007.

[4]R. Harikumar, B.Vinoth Kumar, G.Karthick, Performance Analysis for Quality Measures Using K means Clustering and EM models in Segmentation of Medical Images, International Journal of Soft Computing and Engineering, Volume-1, Issue-6, January 2012.

[5]Feng Zhao, Licheng Jiao, Spatial improved fuzzy c-means clustering for image segmentation, International Conference on Electronic and Mechanical Engineering and Information Technology, IEEE 2011, pp 4791-4794.

[6]Keh-Shih Chuang, Hong-Long Tzeng, Sharon Chen, Jay Wu, Tzong-Jer Chen, Fuzzy c-means clustering with spatial information for image segmentation, Computerized Medical Imaging and Graphics, 2006, pp 9-15.

[7]Zhenping Xie Shitong Wang, A New Level Set Method For Image Segmentation Integrated with FCM, Fourth International Conference on Fuzzy Systems and Knowledge Discovery, IEEE Computer Society- 2007.


[9]Chuang KS, Hzeng HL, Chen S, Wu J, Chen TJ, Fuzzy c-means clustering with spatial information for image segmentation, Computerized Medical Imaging and Graphics. 2006, pp. 9–15.

[10]Cai W, Chen S, Zhang D, Fast and robust fuzzy c-means clustering algorithms incorporating local information for image segmentation, Pattern Recognition. 2007, pp. 825–838.

[11]Micael S. Couceiro, Rui P. Rocha, N. M. Fonseca Ferreira1 and J. A. Tenreiro Machado, Introducing the Fractional Order Darwinian PSO, Springer London Volume 1 / 2007 - Volume 6 / 2012.

[12]Ortigueira, M. D., & Tenreiro Machado, J. A., Special Issue on Fractional Signal Processing, Signal Process, 2003 83, 2285- 2480.

[13]Pires, E.J.S., Machado, J.A.T., Oliveira, P.B.M., Cunha, J.B. and Mendes, L., Particle swarm optimization with fractional-order velocity, Journal on Nonlinear Dynamics, 2010, 61: 295–301.

[14]Yasuda, K., Iwasaki, N., Ueno, G. and Aiyoshi, E. Particle Swarm Optimization: A Numerical Stability Analysis and Parameter Adjustment Based on Swarm Activity, IEEJ Transactions on Electrical and Electronic Engineering, Wiley InterScience, 2008, vol. 3, pp. 642-659.

[15]Shi, Y. and Eberhart, R., Fuzzy adaptive particle swarm optimization. In Proc. IEEE Congr. Evol. Comput., 2001, vol. 1, pp. 101–106.

[16]S. Thilagamani1 and N. Shanthi, A Survey on Image Segmentation Through Clustering, International Journal of Research and Reviews in Information Sciences, Vol. 1, No. 1, March 2011 pp 14-17.