A novel robust and fast Segmentation of the Color Images using Fuzzy Classification C-means
| dc.contributor.author | Musau, Felix | |
| dc.contributor.author | Toure, Mohamed Lamine | |
| dc.contributor.author | Beiji, Zou | |
| dc.date.accessioned | 2024-08-14T07:03:58Z | |
| dc.date.available | 2024-08-14T07:03:58Z | |
| dc.date.issued | 2010 | |
| dc.description.abstract | This paper brings out a method for segmentation of color images based on fuzzy classification. It proceeds in a first step by a fine segmentation using the algorithm of fuzzy cmeans (FCM). The method then applies a test fusion of fuzzy classes. The result is a coarse segmentation, where each region is the union of elementary regions grown from FCM. The fuzzy C-Means (FCM) clustering is an iterative partitioning method that produces optimal c-partitions, the standard FCM algorithm takes a long time to partition a large data set. The proposed FCM program must read the entire data set into a memory for processing. Our results show that the system performance is robust to different types of images. | |
| dc.identifier.citation | Toure, M. L., Beiji, Z., & Musau, F. (2010). A novel robust and fast Segmentation of the Color Images using Fuzzy Classification C-means. In 2nd International Conforence on Education Technology and Computer (ICETC), pp. V4-341-V4-344. https://doi: 10.1109/ICETC.2010.5529667. | |
| dc.identifier.uri | https://repository.ru.ac.ke/handle/123456789/53 | |
| dc.language.iso | en | |
| dc.publisher | IEEE | |
| dc.relation.ispartofseries | 2nd International Conforence on Education Technology and Computer (ICETC) | |
| dc.subject | Segmentation | |
| dc.subject | Classification | |
| dc.subject | FUZlJ'Logic | |
| dc.subject | FCM | |
| dc.subject | Merge regions | |
| dc.subject | Optimal c-partitions. | |
| dc.title | A novel robust and fast Segmentation of the Color Images using Fuzzy Classification C-means | |
| dc.type | Article |