A dynamic niching clustering algorithm based on individual-connectedness and its application to color image segmentation
文献类型：期刊论文
| 作者 | Chang, DX ; Zhao, Y ; Liu, L ; Zheng, CW |
| 刊名 | PATTERN RECOGNITION
 |
| 出版日期 | 2016 |
| 卷号 | 60页码:334-347 |
| 关键词 | Clustering Genetic algorithms Niching Connected individual k-distance neighborhood Image segmentation |
| ISSN号 | 0031-3203 |
| 中文摘要 | In this paper, a dynamic niching clustering algorithm based on individual-connectedness (DNIC) is proposed for unsupervised classification with no prior knowledge. It aims to automatically evolve the optimal number of clusters as well as the cluster centers of the data set based on the proposed adaptive compact k-distance neighborhood algorithm. More specifically, with the adaptive selection of the number of the nearest neighbor and the individual-connectedness algorithm, DNIC often achieves several sets of connecting individuals and each set composes an independent niche. In practice, each set of connecting individuals corresponds to a homogeneous cluster and this ensures the separability of an arbitrary data set theoretically. An application of the DNIC clustering algorithm in color image segmentation is also provided. Experimental results demonstrate that the DNIC clustering algorithm has high performance and flexibility. (C) 2016 Elsevier Ltd. All rights reserved. |
| 英文摘要 | In this paper, a dynamic niching clustering algorithm based on individual-connectedness (DNIC) is proposed for unsupervised classification with no prior knowledge. It aims to automatically evolve the optimal number of clusters as well as the cluster centers of the data set based on the proposed adaptive compact k-distance neighborhood algorithm. More specifically, with the adaptive selection of the number of the nearest neighbor and the individual-connectedness algorithm, DNIC often achieves several sets of connecting individuals and each set composes an independent niche. In practice, each set of connecting individuals corresponds to a homogeneous cluster and this ensures the separability of an arbitrary data set theoretically. An application of the DNIC clustering algorithm in color image segmentation is also provided. Experimental results demonstrate that the DNIC clustering algorithm has high performance and flexibility. (C) 2016 Elsevier Ltd. All rights reserved. |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000383525600028 |
| 公开日期 | 2016-12-09 |
| 源URL | [http://ir.iscas.ac.cn/handle/311060/17290]  |
| 专题 | 软件研究所_软件所图书馆_期刊论文 |
| 推荐引用方式 GB/T 7714 | Chang, DX,Zhao, Y,Liu, L,et al. A dynamic niching clustering algorithm based on individual-connectedness and its application to color image segmentation[J]. PATTERN RECOGNITION,2016,60:334-347. |
| APA | Chang, DX,Zhao, Y,Liu, L,&Zheng, CW.(2016).A dynamic niching clustering algorithm based on individual-connectedness and its application to color image segmentation.PATTERN RECOGNITION,60,334-347. |
| MLA | Chang, DX,et al."A dynamic niching clustering algorithm based on individual-connectedness and its application to color image segmentation".PATTERN RECOGNITION 60(2016):334-347. |
入库方式： OAI收割
来源：软件研究所
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