Name
Abstract | ||
|---|---|---|
The clustering methods based on Fuzzy C-Means (FCM) are frequently used in image-segmentation. But the standard FCM algorithm has some defects, especially ignoring the pixel spatial information's influence on the classification result. For the sake of a more reasonable objective function, an improved FCM algorithm is proposed in this paper, which uses spatial information and S-function to determine the weight coefficients of the objective function. Experimental results show that the proposed algorithm has better performance than the standard FCM algorithm. © 2011 IEEE. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/FSKD.2011.6019882 | FSKD |
Keywords | Field | DocType |
fuzzy c-means,image segmentation,s-function,spatial information,fuzzy set theory,algorithm design,objective function,clustering algorithms,fuzzy clustering,classification algorithms,correlation,indexes,algorithm design and analysis,indexation,edge detection | Fuzzy clustering,Data mining,Computer science,Fuzzy set,Image segmentation,Artificial intelligence,Cluster analysis,Algorithm design,Pattern recognition,Fuzzy logic,Algorithm,Pixel,Statistical classification,Machine learning | Conference |
Volume | Issue | Citations |
3 | null | 0 |
PageRank | References | Authors |
0.34 | 4 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Maokai Yuan | 1 | 0 | 0.34 |
| Liping Chen | 2 | 60 | 10.10 |
| Jianqiang Wang | 3 | 8 | 3.40 |
| Shuguang Zhao | 4 | 111 | 12.82 |