Referenced Items are not available for this document.
A novel approach for enhancing the results of fuzzy clustering by imposing spatial constraints for solving image segmentation problems is presented. We have developed a Sugeno (185) type rule-based system with three inputs and 11 rules that interacts with the clustering results obtained by the well-known fuzzy c-means (FCM) and/or possibilistic c-means (PCM) algorithms. It provides good image segmentations in terms of region smoothness and elimination of the effects of noise. The results of the proposed rule-based neighborhood enhancement (RB-NE) system are compared to well-known segmentation algorithms using stochastic field modeling. They are found to be of comparable quality, while being of lower computational complexity.
Published in:
Signal Processing Letters, IEEE
(Volume:5
,
Issue:
10
)
Date of Publication: Oct. 1998
- Page(s):
- 245 - 247
- ISSN :
- 1070-9908
- INSPEC Accession Number:
- 6063313
- Digital Object Identifier :
- 10.1109/97.720555
- Product Type:
- Journals & Magazines
- Date of Current Version :
- 06 August 2002
- Issue Date :
- Oct. 1998
- Sponsored by :
- IEEE Signal Processing Society
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