Automated sunspot detection using morphological reconstruction and adaptive region growing techniques
文献类型：会议论文
| 作者 | Yu, Lan1; Deng LH(邓林华)2 ; Feng, Song3
|
| 出版日期 | 2014-09-11 |
| 会议名称 | Chinese Control Conference, CCC |
| 会议日期 | 2014-07-28 |
| 会议地点 | Nanjing, China |
| 关键词 | Automated detection, Sunspot umbrae, Sunspot penumbrae, Morphological reconstruction, Adaptive region growing |
| 页码 | 7168-7172 |
| 通讯作者 | Yu, Lan |
| 英文摘要 | Sunspots are dark areas with respect to their surrounding area because the temperature of sunspot areas is lower than the average temperature of the solar surface. It provides essential information for many aspects of solar physics. A sunspot is composed of umbra and penumbra. It is a prerequisite for studying solar physics and spatial atmosphere to accurately segment and extract sunspot structures. Consequently, we propose an automated detection technique for segmenting and extracting them. The detection procedure is composed of two steps: (1) segmenting and extracting sunspot umbra with morphological reconstruction; (2) detecting and segmenting sunspot penumbra with region growing. For evaluating the accuracy of the detection procedure, we used a high-resolution observation obtained by Solar Optical Telescope onboard Hinode, and other obtained with the Dutch Open Telescope to illustrate the performance. The results demonstrate that our proposed technique is significant effective and accurate, and is suitable for studying the sunspot evolution and their physical phenomena. |
| 收录类别 | EI ; CPCI |
| 产权排序 | 第2完成单位 |
| 会议网址 | http://ieeexplore.ieee.org/document/6896184/ |
| 会议录 | Proceedings of the 33rd Chinese Control Conference, CCC 2014
 |
| 会议录出版者 | IEEE Computer Society |
| 学科主题 | Automation & Control Systems |
| 会议录出版地 | 345 E 47TH ST, NEW YORK, NY 10017 USA |
| 语种 | 英语 |
| ISSN号 | 2161-2927 |
| ISBN号 | 9789881563842 |
| WOS记录号 | WOS:000366482807052 |
| 研究领域[WOS] | Automation & Control Systems |
| 源URL | [http://ir.ynao.ac.cn/handle/114a53/4877]  |
| 专题 | 云南天文台_抚仙湖太阳观测站 |
| 作者单位 | 1.Department of Information Engineering, Yunnan Land and Resources Vocational College, Kunming 650217, P. R. China 2.National Astronomical Observatories/ Yunnan Astronomical Observatory, Chinese Academy of Sciences, Kunming 650011, P. R. China 3.Yunnan Key Laboratory of Computer Technology Application / Faculty of Information Engineering and Automation, Kunming. University of Science and Technology, Kunming 650500, P. R. China |
| 推荐引用方式 GB/T 7714 | Yu, Lan,Deng LH,Feng, Song. Automated sunspot detection using morphological reconstruction and adaptive region growing techniques[C]. 见:Chinese Control Conference, CCC. Nanjing, China. 2014-07-28.http://ieeexplore.ieee.org/document/6896184/. |
入库方式： OAI收割
来源：云南天文台
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