Image Segmentation Based on the Ant Colony and Improved FCMClustering Algorithm with Spatial Information
[1]MAO Xiaobo,ZHANG Yongjie,CHEN Tiejun.Image Segmentation Based on the Ant Colony and Improved FCMClustering Algorithm with Spatial Information[J].Journal of Zhengzhou University (Engineering Science),2014,35(01):1-4.[doi:10.3969/j.issn.1671-6833.2014.01.001]
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Journal of Zhengzhou University (Engineering Science)[ISSN
1671-6833/CN
41-1339/T] Volume:
35
Number of periods:
2014 01
Page number:
1-4
Column:
Public date:
2014-02-28
- Title:
- Image Segmentation Based on the Ant Colony and Improved FCMClustering Algorithm with Spatial Information
- Keywords:
- ant colony algorithm; watershed; spalial information ; image segmentation
- CLC:
- -
- DOI:
- 10.3969/j.issn.1671-6833.2014.01.001
- Abstract:
- With the fuzzy C-means clustering (FCM ) algorithm it is diffieult to determine the number of clus.ters on image segmentation, which is easy to get into a local oplimum. In order to solve the problems, this pa-per proposed a new segmentation method based on the ant eolony and improved FCM Clustering Algorithm withspatial information. Dividing image with the help of watershed algorithm, we got the initial segmentation re.sults. lt made full use of the ability of global optimization of the ant eolony algorithm to obtain the aeeurate o-riginal cluster centers and eluster number. Then the results were obtained as the iniial cluster eenters and thenumber of clusters of fuzzy C-means clustering algorihm. The experimental results show that: due to the de.erease of the size of clustering samples, the clustering speed, noise immunity and the robustness of the algo.rithm are improved signifcantly.
- References:
- -
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