Extraction of visual texture features of seabed sediments using an SVDD approach
文献类型：期刊论文
| 作者 | Li Y(李岩) ; Liu SJ(刘世杰); Zhu PQ(祝普强); Yu JC(俞建成); Li S(李硕)
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| 刊名 | OCEAN ENGINEERING
 |
| 出版日期 | 2017 |
| 卷号 | 142页码:501-506 |
| 关键词 | Support Vector Domain Description Classification Of Seabed Sediments Texture Features Analysis Perception Of Seabed Environment Gray-level Co-occurrence Matrix Self-organizing Map |
| ISSN号 | 0029-8018 |
| 产权排序 | 1 |
| 英文摘要 | Perception of the seabed environment is an important capability of autonomous underwater vehicles. This paper focuses on defining and extracting robust texture features from visual images that lead to useful and practical automated identification of the types of seabed sediments. The visual texture features are described by using a gray-level co-occurrence matrix (GLCM) and fractal dimension, after which an unsupervised learning method, self-organizing map (SOM), is adopted to evaluate the validity of features descriptors on three types of seabed sediments. Subsequently, a kernel-based approach that exhibits robustness versus low numbers of high dimensional samples, named support vector domain description (SVDD), is applied to classify the types of seabed sediments. In comparison with state-of-the-art classifiers, the experimental results demonstrated the effectiveness of the SVDD on the classification of seabed sediments. |
| WOS关键词 | VECTOR DATA DESCRIPTION ; CLASSIFICATION ; DISCRIMINATION ; DIMENSION ; HABITAT ; ROXANN ; IMAGE |
| WOS研究方向 | Engineering ; Oceanography |
| 语种 | 英语 |
| WOS记录号 | WOS:000410010700044 |
| 资助机构 | National Key Research and Development Program of China [2016YFC0300801] ; "R & D Center for Underwater Construction Robotics," - Ministry of Ocean and Fisheries (MOF) ; Korea Institute of Marine Science & Technology Promotion (KIMST), Korea [PJT200539] ; National Natural Science Foundation [61233013, 41376110] ; State Key Laboratory of Robotics at Shenyang Institute of Automation [2013-Z13] |
| 源URL | [http://ir.sia.cn/handle/173321/21003]  |
| 专题 | 海洋机器人卓越创新中心 |
| 通讯作者 | Li S(李硕) |
| 作者单位 | 1.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China 2.University of Chinese Academy of Sciences, Beijing, China |
| 推荐引用方式 GB/T 7714 | Li Y,Liu SJ,Zhu PQ,et al. Extraction of visual texture features of seabed sediments using an SVDD approach[J]. OCEAN ENGINEERING,2017,142:501-506. |
| APA | Li Y,Liu SJ,Zhu PQ,Yu JC,&Li S.(2017).Extraction of visual texture features of seabed sediments using an SVDD approach.OCEAN ENGINEERING,142,501-506. |
| MLA | Li Y,et al."Extraction of visual texture features of seabed sediments using an SVDD approach".OCEAN ENGINEERING 142(2017):501-506. |
入库方式： OAI收割
来源：沈阳自动化研究所
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