Name
Abstract | ||
|---|---|---|
FCM algorithm is a classic algorithm applied to image segmentation during the processing of medical images. This article aims at a further study of the traditional FCM algorithm, including testing and improving the cluster category, weighting exponent and other elements which may influence the result of image segmentation. And for the image segmentation steps of FCM algorithm, we correct the maximum fuzzy membership of samples in the iteration. Then, we compare and analyse the results of the traditional algorithm and the improved one. The outcome demonstrates that the improved algorithm greatly improves the result of image segmentation. The improved algorithm makes an ideal achievement in practise. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1007/978-3-642-23756-0_70 | ADVANCES IN COMPUTER SCIENCE, INTELLIGENT SYSTEM AND ENVIRONMENT, VOL 2 |
Keywords | Field | DocType |
FCM,Medical Image,Image Segmentation,Membership | Weighting,Scale-space segmentation,Pattern recognition,Computer science,Fuzzy logic,Image segmentation,Artificial intelligence | Conference |
Volume | Issue | ISSN |
105 | null | 1867-5662 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhanfang Chen | 1 | 0 | 1.69 |
| Huamin Yang | 2 | 19 | 17.29 |
| GuoYu Zhang | 3 | 0 | 0.68 |
| WeiLi Shi | 4 | 1 | 5.10 |