| An integrated aurora image retrieval system: AuroraEye | |
| Fu, Rong2; Gao, Xinbo2; Li, Xuelong3; Tao, Dacheng1; Jian, Yongjun2; Li, Jie2; Hu, Hongqiao4; Yang, Huigen4; D. Tao | |
| 2010-11-01 | |
| 发表期刊 | JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION
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| ISSN | 1047-3203 |
| 卷号 | 21期号:8页码:787-797 |
| 摘要 | With the digital all-sky imager (ASI) emergence in aurora research, millions of images are captured annually. However, only a fraction of which can be actually used. To address the problem incurred by low efficient manual processing, an integrated image analysis and retrieval system is developed. For precisely representing aurora image, macroscopic and microscopic features are combined to describe aurora texture. To reduce the feature dimensionality of the huge dataset, a modified local binary pattern (LBP) called ALBP is proposed to depict the microscopic texture, and scale-invariant Gabor and orientation-invariant Gabor are employed to extract the macroscopic texture. A physical property of aurora is inducted as region features to bridge the gap between the low-level visual features and high-level semantic description. The experiments results demonstrate that the ALBP method achieves high classification rate and low computational complexity. The retrieval simulation results show that the developed retrieval system is efficient for huge dataset. (c) 2010 Elsevier Inc. All rights reserved. |
| 文章类型 | Article |
| 关键词 | Content-based Image Retrieval Aurora Adaptive Lbp Gabor Image Texture Analysis Database Feature Extraction Local Binary Pattern |
| 学科领域 | 信号与模式识别 |
| WOS标题词 | Science & Technology ; Technology |
| DOI | 10.1016/j.jvcir.2010.06.002 |
| 收录类别 | SCI ; EI |
| 关键词[WOS] | SUPPORT VECTOR MACHINES ; RELEVANCE FEEDBACK ; SELECTION ; SUBSPACE ; TENSOR |
| 语种 | 英语 |
| WOS研究方向 | Computer Science |
| WOS类目 | Computer Science, Information Systems ; Computer Science, Software Engineering |
| WOS记录号 | WOS:000283827500003 |
| 引用统计 | |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://ir.opt.ac.cn/handle/181661/8562 |
| 专题 | 光谱成像技术研究室 |
| 通讯作者 | D. Tao |
| 作者单位 | 1.Nanyang Technol Univ, Sch Comp Engn, Singapore 639798, Singapore 2.Xidian Univ, Sch Elect Engn, Xian 710071, Peoples R China 3.Chinese Acad Sci, Ctr OPT IMagery Anal & Learning OPTIMAL, State Key Lab Transient Opt & Photon, Xian Inst Opt & Precis Mech, Xian 710779, Peoples R China 4.Polar Res Inst China, SOA Key Lab Polar Sci, Shanghai 200136, Peoples R China |
| 推荐引用方式 GB/T 7714 | Fu, Rong,Gao, Xinbo,Li, Xuelong,et al. An integrated aurora image retrieval system: AuroraEye[J]. JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION,2010,21(8):787-797. |
| APA | Fu, Rong.,Gao, Xinbo.,Li, Xuelong.,Tao, Dacheng.,Jian, Yongjun.,...&D. Tao.(2010).An integrated aurora image retrieval system: AuroraEye.JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION,21(8),787-797. |
| MLA | Fu, Rong,et al."An integrated aurora image retrieval system: AuroraEye".JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION 21.8(2010):787-797. |
| 条目包含的文件 | ||||||
| 文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
| An integrated aurora（1400KB） | 期刊论文 | 出版稿 | 限制开放 | CC BY-NC-SA | 请求全文 | |
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