{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,19]],"date-time":"2026-05-19T10:36:15Z","timestamp":1779186975069,"version":"3.51.4"},"reference-count":24,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2020,3,18]],"date-time":"2020-03-18T00:00:00Z","timestamp":1584489600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the National Science Foundation of China","award":["51579204"],"award-info":[{"award-number":["51579204"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>For the navigation of an unmanned surface vehicle (USV), detection and recognition of the water-shore-line (WSL) is an important part of its intellectualization. Current research on this issue mainly focuses on the straight WSL obtained by straight line fitting. However, the WSL in the image acquired by boat-borne vision is not always in a straight line, especially in an inland river waterway. In this paper, a novel three-step approach for WSL detection is therefore proposed to solve this problem through the information of an image sequence. Firstly, the initial line segment pool is built by the line segment detector (LSD) algorithm. Then, the coarse-to-fine strategy is used to obtain the onshore line segment pool, including the rough selection of water area instability and the fine selection of the epipolar constraint between image frames, both of which are demonstrated in detail in the text. Finally, the complete shore area is generated by an onshore line segment pool of multi-frame images, and the lower boundary of the area is the desired WSL. In order to verify the accuracy and robustness of the proposed method, field experiments were carried out in the inland river scene. Compared with other detection algorithms based on image processing, the results demonstrate that this method is more adaptable, and can detect not only the straight WSL, but also the curved WSL.<\/jats:p>","DOI":"10.3390\/s20061682","type":"journal-article","created":{"date-parts":[[2020,3,19]],"date-time":"2020-03-19T03:54:14Z","timestamp":1584590054000},"page":"1682","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":27,"title":["A Novel Water-Shore-Line Detection Method for USV Autonomous Navigation"],"prefix":"10.3390","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1008-0935","authenticated-orcid":false,"given":"Xiong","family":"Zou","sequence":"first","affiliation":[{"name":"School of Navigation, Wuhan University of Technology, Wuhan 430063, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9286-2094","authenticated-orcid":false,"given":"Changshi","family":"Xiao","sequence":"additional","affiliation":[{"name":"School of Navigation, Wuhan University of Technology, Wuhan 430063, China"},{"name":"Hubei Key Laboratory of Inland Shipping Technology, Wuhan 430063, China"},{"name":"National Engineering Research Center for Water Transport Safety, Wuhan 430063, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9003-0478","authenticated-orcid":false,"given":"Wenqiang","family":"Zhan","sequence":"additional","affiliation":[{"name":"School of Navigation, Wuhan University of Technology, Wuhan 430063, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chunhui","family":"Zhou","sequence":"additional","affiliation":[{"name":"School of Navigation, Wuhan University of Technology, Wuhan 430063, China"},{"name":"National Engineering Research Center for Water Transport Safety, Wuhan 430063, China"},{"name":"Intelligent Transportation Systems Research Center, Wuhan 430063, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Supu","family":"Xiu","sequence":"additional","affiliation":[{"name":"School of Navigation, Wuhan University of Technology, Wuhan 430063, China"},{"name":"Intelligent Transportation Systems Research Center, Wuhan 430063, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5609-4558","authenticated-orcid":false,"given":"Haiwen","family":"Yuan","sequence":"additional","affiliation":[{"name":"School of Navigation, Wuhan University of Technology, Wuhan 430063, China"},{"name":"National Engineering Research Center for Water Transport Safety, Wuhan 430063, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,3,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"5","DOI":"10.2478\/pomr-2018-0016","article-title":"Automatic watercraft recognition and identification on water areas covered by video monitoring as extension for sea and river traffic supervision systems","volume":"25","author":"Wawrzyniak","year":"2018","journal-title":"Pol. 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