A new method for image segmentation based on Fuzzy C-means algorithm on pixonal images formed by bilateral filtering

1. Bonnet N., Cutrona J., Herbin M.: A ‘no-threshold’ histogram- based image segmentation method. Pattern Recognit. 35(10), 2319–2322 (2002)

   Article  MATH  Google Scholar 

2. Shih F.Y., Cheng S.: Automatic seeded region growing for color image segmentation. Image Vis. Comput. 23, 877–886 (2005)

   Article  Google Scholar 

3. Gonzalez R.C., Woods R.E.: Digital Image Processing. Prentice Hall, Englewood Cliffs (2004)

   Google Scholar 

4. Papamichail G.P., Papamichail D.P.: The k-means range algorithm for personalized data clustering in e-Commerce. Eur. J. Oper. Res. 177(3), 1400–1408 (2007)

   Article  MATH  Google Scholar 

5. Carvalho A.T.F.: Fuzzy C-means clustering methods for symbolic interval data. Pattern Recognit. Lett. 28(4), 423–437 (2007)

   Article  MathSciNet  Google Scholar 

6. Clausi D.A.: K-means iterative fisher (KIF) unsupervised clustering algorithm applied to image texture segmentation. Pattern Recognit. 35(9), 1959–1972 (2002)

   Article  MATH  Google Scholar 

7. Comaniciu D., Meer P.: Mean shift: a robust approach toward feature space analysis. IEEE Trans. Pattern Anal. Mach. Intell. 24(5), 1–18 (2002)

   Article  Google Scholar 

8. Kato Z., Pong T.C.: A markov random field image segmentation model for color textured images. Image Vis. Comput. 24(10), 1103–1114 (2006)

   Article  Google Scholar 

9. Hochbaum D.S.: An efficient algorithm for image segmentation, Markov random fields and related problems. J. ACM. 48(4), 686–701 (2001)

   Article  MathSciNet  MATH  Google Scholar 

10. Kato Z., Zerubia J., Berthod M.: Unsupervised parallel image classification using markovian models. Pattern Recognit. 32, 591–604 (1999)

    Article  Google Scholar 

11. Piña R.K., Pueter R.C.: Bayesian image reconstruction: the pixon and optimal image modeling. P. A. S. P. 105, 630–637 (1993)

    Article  Google Scholar 

12. Puetter R.C.: Pixon-based multiresolution image reconstruction and the quantification of figure information content. Int. J Imaging Syst. Technol. 6, 314–331 (1995)

    Article  Google Scholar 

13. Yang F., Jiang T.: Pixon-based image segmentation with markov random fields. IEEE Trans. Image Process. 12(12), 1552–1559 (2003)

    Article  MathSciNet  Google Scholar 

14. Lin L., Zhu L., Yang F., Jiang T.: A novel pixon-representation for image segmentation based on markov random field. Image Vis. Comput. 26, 1507–1514 (2008)

    Article  Google Scholar 

15. Paris S., Kornprobst P., Tumblin J.: Bilateral Filtering. Now Publishers, Hanover (2009)

    Google Scholar 

16. Tomasi, C., Manduchi, R.: Bilateral filtering for gray and color images. In: Proceedings of the IEEE International Conference on Computer Vision. Bombay, (1998)

17. Chuang K.S., Tzeng H.L., Chen S., Wu J., Chen T.J.: Fuzzy C-means clustering with spatial information for image segmentation. Comput. Med. Imaging Graph. 30(1), 9–15 (2006)

    Article  Google Scholar 

18. Chuai-aree S., Lursinsap C., Sophatsathit P., Siripant S.: Fuzzy C-mean: a statistical feature classification of text and image segmentation method. Inte. J. Uncertain. Fuzziness Knowl. Based Syst. 9(6), 661–671 (2001)

    MATH  Google Scholar 

19. Lu, Q., Jiang, T.: Pixon-based image segmentation with markov random fields. In: Proceeding of the Asian Conference on Computer Vision. Melbourne, Australia, pp. 23–25 (2002)

20. Gonzalez, R.C., Woods, R.E.: Image Databases [Online], available at: <http://www.imageprocessingplace.com> Accessed August 2010

Download references