Hydrographic data inspection and disaster monitoring using shipborne radar small range images with electronic navigation chart

Jin Xu; Baozhu Jia; Xinxiang Pan; Ronghui Li; Liang Cao; Can Cui; Haixia Wang; Bo Li

doi:10.7717/peerj-cs.290

Hydrographic data inspection and disaster monitoring using shipborne radar small range images with electronic navigation chart

PeerJ Comput Sci. 2020 Sep 14:6:e290. doi: 10.7717/peerj-cs.290. eCollection 2020.

Authors

Jin Xu^#^{1

2}, Baozhu Jia^#¹, Xinxiang Pan^{1

3}, Ronghui Li¹, Liang Cao¹, Can Cui⁴, Haixia Wang², Bo Li^{1

5}

Affiliations

¹ Maritime College, Guangdong Ocean University, Zhanjiang, Guangdong, China.
² Navigation College, Dalian Martime University, Dalian, Liaoning, China.
³ Marine Engineering College, Dalian Maritime University, Dalian, Liaoning, China.
⁴ Civil Aviation College, Shenyang Aerospace University, Shenyang, Liaoning, China.
⁵ Laboratory Department, Liaoning Hydrogeology and Engineering Geology Reconnaissance Institute, Dalian, China.

^# Contributed equally.

Abstract

Shipborne radars cannot only enable navigation and collision avoidance but also play an important role in the fields of hydrographic data inspection and disaster monitoring. In this paper, target extraction methods for oil films, ships and coastlines from original shipborne radar images are proposed. First, the shipborne radar video images are acquired by a signal acquisition card. Second, based on remote sensing image processing technology, the radar images are preprocessed, and the contours of the targets are extracted. Then, the targets identified in the radar images are integrated into an electronic navigation chart (ENC) by a geographic information system. The experiments show that the proposed target segmentation methods of shipborne radar images are effective. Using the geometric feature information of the targets identified in the shipborne radar images, information matching between radar images and ENC can be realized for hydrographic data inspection and disaster monitoring.

Keywords: Electronic navigation chart; Information fusion; Oil spill; Shipborne radar.

Grants and funding

This research was funded by the National Natural Science Foundation of China (Nos. 51709031,51979045), the Fundamental Research Funds for the Central Universities (No. 3132019138), the Innovation Support Project of Dalian (No. 2018RQ22), the Enterprise-university-research Cooperation Project of the Ministry of Education of China (No. 201702043016), the Special projects in key fields (Artificial Intelligence) of Universities in Guangdong Province (No. 2019KZDZX1035) and program for scientific research start-up funds of Guangdong Ocean University. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.