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Monocular Vision-Based Underwater Object Detection
Chen, Zhe; Zhang, Zhen; Dai, Fengzhao; Bu, Yang; Wang, Huibin; chenzhe@hhu.edu.cn; zz_hhuc@hhu.edu.cn; fzdai@siom.ac.cn; buyang@siom.ac.cn; hbwang@hhu.edu.cn
2017
Source PublicationSensors
Volume17Issue:8
AbstractIn this paper, we propose an underwater object detection method using monocular vision sensors. In addition to commonly used visual features such as color and intensity, we investigate the potential of underwater object detection using light transmission information. The global contrast of various features is used to initially identify the region of interest (ROI), which is then filtered by the image segmentation method, producing the final underwater object detection results. We test the performance of our method with diverse underwater datasets. Samples of the datasets are acquired by a monocular camera with different qualities (such as resolution and focal length) and setups (viewing distance, viewing angle, and optical environment). It is demonstrated that our ROI detection method is necessary and can largely remove the background noise and significantly increase the accuracy of our underwater object detection method.
SubtypeArticle
Department信息光电
DOI10.3390/s17081784
Funding OrganizationNational Natural Science Foundation of China [61501173, 61671201]; Natural Science Foundation of Jiangsu Province [BK20150824]; Fundamental Research Funds for the Central Universities [2017B01914]; Jiangsu Overseas Scholar Program for University Prominent Young & Middle-aged Teachers and Presidents ; National Natural Science Foundation of China [61501173, 61671201]; Natural Science Foundation of Jiangsu Province [BK20150824]; Fundamental Research Funds for the Central Universities [2017B01914]; Jiangsu Overseas Scholar Program for University Prominent Young & Middle-aged Teachers and Presidents ; National Natural Science Foundation of China [61501173, 61671201]; Natural Science Foundation of Jiangsu Province [BK20150824]; Fundamental Research Funds for the Central Universities [2017B01914]; Jiangsu Overseas Scholar Program for University Prominent Young & Middle-aged Teachers and Presidents ; National Natural Science Foundation of China [61501173, 61671201]; Natural Science Foundation of Jiangsu Province [BK20150824]; Fundamental Research Funds for the Central Universities [2017B01914]; Jiangsu Overseas Scholar Program for University Prominent Young & Middle-aged Teachers and Presidents
Indexed BySCI
Funding OrganizationNational Natural Science Foundation of China [61501173, 61671201]; Natural Science Foundation of Jiangsu Province [BK20150824]; Fundamental Research Funds for the Central Universities [2017B01914]; Jiangsu Overseas Scholar Program for University Prominent Young & Middle-aged Teachers and Presidents ; National Natural Science Foundation of China [61501173, 61671201]; Natural Science Foundation of Jiangsu Province [BK20150824]; Fundamental Research Funds for the Central Universities [2017B01914]; Jiangsu Overseas Scholar Program for University Prominent Young & Middle-aged Teachers and Presidents ; National Natural Science Foundation of China [61501173, 61671201]; Natural Science Foundation of Jiangsu Province [BK20150824]; Fundamental Research Funds for the Central Universities [2017B01914]; Jiangsu Overseas Scholar Program for University Prominent Young & Middle-aged Teachers and Presidents ; National Natural Science Foundation of China [61501173, 61671201]; Natural Science Foundation of Jiangsu Province [BK20150824]; Fundamental Research Funds for the Central Universities [2017B01914]; Jiangsu Overseas Scholar Program for University Prominent Young & Middle-aged Teachers and Presidents
WOS IDWOS:000408576900087
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Cited Times:3[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.siom.ac.cn/handle/181231/27520
Collection信息光学与光电技术实验室
Corresponding Authorchenzhe@hhu.edu.cn; zz_hhuc@hhu.edu.cn; fzdai@siom.ac.cn; buyang@siom.ac.cn; hbwang@hhu.edu.cn
Affiliation中国科学院上海光学精密机械研究所
Recommended Citation
GB/T 7714
Chen, Zhe,Zhang, Zhen,Dai, Fengzhao,et al. Monocular Vision-Based Underwater Object Detection[J]. Sensors,2017,17(8).
APA Chen, Zhe.,Zhang, Zhen.,Dai, Fengzhao.,Bu, Yang.,Wang, Huibin.,...&hbwang@hhu.edu.cn.(2017).Monocular Vision-Based Underwater Object Detection.Sensors,17(8).
MLA Chen, Zhe,et al."Monocular Vision-Based Underwater Object Detection".Sensors 17.8(2017).
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