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

Signal, Image and Video Processing

Volumn 7, Issue 5, 2013, Pages 855-863

  Nadernejad, Ehsan ^a   Sharifzadeh, Sara ^a  

^a TECHNICAL UNIVERSITY OF DENMARK   (Denmark)

Author keywords

Bilateral filtering; Fuzzy C mean; Image segmentation; Pixonal image

Indexed keywords

BILATERAL FILTERING; COMPUTATIONAL LOADS; FUZZY C MEAN; FUZZY C-MEANS ALGORITHMS; HIERARCHICAL CLUSTERING METHODS; IMAGE OVER SEGMENTATIONS; PIXONAL IMAGE; SEGMENTATION TECHNIQUES;

COPYING; FUZZY CLUSTERING; NONLINEAR FILTERING;

IMAGE SEGMENTATION;

EID: 84881549910     PISSN: 18631703     EISSN: 18631711     Source Type: Journal    
DOI: 10.1007/s11760-011-0274-0     Document Type: Article

References (20)

1. Bonnet N., Cutrona J., Herbin M.: A 'no-threshold' histogram- based image segmentation method. Pattern Recognit. 35(10), 2319-2322 (2002).
2. Shih F. Y., Cheng S.: Automatic seeded region growing for color image segmentation. Image Vis. Comput. 23, 877-886 (2005).
3. Gonzalez R. C., Woods R. E.: Digital Image Processing. Prentice Hall, Englewood Cliffs (2004).
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).
5. Carvalho A. T. F.: Fuzzy C-means clustering methods for symbolic interval data. Pattern Recognit. Lett. 28(4), 423-437 (2007).
6. Clausi D. A.: K-means iterative fisher (KIF) unsupervised clustering algorithm applied to image texture segmentation. Pattern Recognit. 35(9), 1959-1972 (2002).
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).
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).
9. Hochbaum D. S.: An efficient algorithm for image segmentation, Markov random fields and related problems. J. ACM. 48(4), 686-701 (2001).
10. Kato Z., Zerubia J., Berthod M.: Unsupervised parallel image classification using markovian models. Pattern Recognit. 32, 591-604 (1999).
11. Piña R. K., Pueter R. C.: Bayesian image reconstruction: the pixon and optimal image modeling. P. A. S. P. 105, 630-637 (1993).
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).
13. Yang F., Jiang T.: Pixon-based image segmentation with markov random fields. IEEE Trans. Image Process. 12(12), 1552-1559 (2003).
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).
15. Paris S., Kornprobst P., Tumblin J.: Bilateral Filtering. Now Publishers, Hanover (2009).
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).
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).
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: Accessed August 2010.