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Robust image segmentation using FCM with spatial constraints based on new kernel-induced distance measure
文献类型：期刊论文
| 作者 | Chen, SC ; Zhang, DQ
|
| 刊名 | IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS
 |
| 出版日期 | 2004-08-01 |
| 卷号 | 34期号:4页码:1907-1916 |
| 关键词 | fuzzy C-means clustering (FCM) image segmentation kernel-induced distance measures kernel methods robustness spatial constraints |
| 英文摘要 | Fuzzy c-means clustering (FCM) with spatial constraints (FCM_S) is an effective algorithm suitable for image segmentation. Its effectiveness contributes not only to the introduction of fuzziness for belongingness of each pixel but also to exploitation of spatial contextual information. Although the contextual information can raise its insensitivity to noise to some extent, FCM_S still lacks enough robustness to noise and outliers and is not suitable for revealing non-Euclidean structure of the input data due to the use of Euclidean distance (L-2 norm). In this paper, to overcome the above problems, we first propose two variants, FCM_S-1 and FCM_S-2, of FCM_S to aim at simplifying its computation and then extend them, including FCM_S, to corresponding robust kernelized versions KFCM_S, KFCM_S-1 and KFCM_S-2 by the kernel methods. Our main motives of using the kernel methods consist in: inducing a class of robust non-Euclidean distance measures for the original data space to derive new objective functions and thus clustering the non-Euclidean structures in data; enhancing robustness of the original clustering algorithms to noise and outliers, and still retaining computational simplicity. The experiments on the artificial and real-world datasets show that our proposed algorithms, especially with spatial constraints, are more effective. |
| WOS标题词 | Science & Technology ; Technology |
| 类目[WOS] | Automation & Control Systems ; Computer Science, Artificial Intelligence ; Computer Science, Cybernetics |
| 研究领域[WOS] | Automation & Control Systems ; Computer Science |
| 关键词[WOS] | C-MEANS ALGORITHM ; FUZZY CLUSTERING-ALGORITHM ; PATTERN-RECOGNITION ; MRI DATA ; SYSTEMS |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000222721000025 |
| 公开日期 | 2015-12-24 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/9990]  |
| 专题 | 自动化研究所_09年以前成果 |
| 作者单位 | 1.Nanjing Univ Aeronaut & Astronaut, Dept Comp Sci & Engn, Nanjing 210016, Peoples R China 2.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100080, Peoples R China 3.Nanjing Univ Aeronaut & Astronaut, Dept Comp Sci & Engn, Nanjing 210016, Peoples R China |
| 推荐引用方式 GB/T 7714 | Chen, SC,Zhang, DQ. Robust image segmentation using FCM with spatial constraints based on new kernel-induced distance measure[J]. IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS,2004,34(4):1907-1916. |
| APA | Chen, SC,&Zhang, DQ.(2004).Robust image segmentation using FCM with spatial constraints based on new kernel-induced distance measure.IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS,34(4),1907-1916. |
| MLA | Chen, SC,et al."Robust image segmentation using FCM with spatial constraints based on new kernel-induced distance measure".IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS 34.4(2004):1907-1916. |
入库方式： OAI收割
来源：自动化研究所
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