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题名: A Novel Visual Classification Method of Seabed Sediments
作者: Li Y(李岩) ; Xia, Chunlei ; Zhu PQ(祝普强) ; Huang Y(黄琰) ; Ge LY(葛利亚)
作者部门: 水下机器人研究室
会议名称: OCEANS'14 MTS/IEEE St. John's
会议日期: September 14-19, 2014
会议地点: St. John's, Canada
会议录: OCEANS'14 MTS/IEEE St. John's
会议录出版者: IEEE
会议录出版地: Piscataway, NJ, USA
出版日期: 2014
页码: 1-4
收录类别: EI
ISBN号: 978-1-4799-4918-2
关键词: seabed images ; fractal dimension ; gray-level cooccurrence matrix ; self-organizing map ; underwater vehicle ; robot vision
摘要: This study aims at the autonomous seafloor surveillance by underwater vehicles based on computer vision techniques. A novel scheme of seabed image classification is proposed to identify three types of seabed sediments. The texture features of seabed sediments were described by using gray-level co-occurrence matrix and fractal dimension. Subsequently, an unsupervised learning method, Self-Organizing Map, was applied to analyze the seabed images with the extracted texture features. The experimental results demonstrated that the proposed texture feature descriptors were feasible and effective to category the three types of seabed images.
产权排序: 1
内容类型: 会议论文
URI标识: http://ir.sia.cn/handle/173321/15307
Appears in Collections:水下机器人研究室_会议论文

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