{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,21]],"date-time":"2026-01-21T14:16:44Z","timestamp":1769005004205,"version":"3.49.0"},"reference-count":19,"publisher":"World Scientific Pub Co Pte Ltd","issue":"02","funder":[{"name":"Natural science foundation of Hubei province, China: Research of automatic detection of underwater small target","award":["2017CFB524"],"award-info":[{"award-number":["2017CFB524"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Patt. Recogn. Artif. Intell."],"published-print":{"date-parts":[[2021,2]]},"abstract":"<jats:p> In synthetic aperture sonar (SAS) image, the underwater shipwreck targets are often buried by sediment or badly damaged. Only a part of the characteristics of artificial objects is retained. In this paper, firstly, based on the analysis of the ocean buried background, the Meanshift filtering is used to smooth the original image and convert the color image into binary one. Secondly, the residual contour of artificial target is extracted through the modified Canny edge detection algorithm. Thirdly, the Region Growing method is taken to remove the discrete interference and keep the intact edge of the line. Consideration with the principle of line alignment, the contours of shipwreck targets are gradually connected and aggregated. Finally, a large amount of measured practical SAS images are tested. The experimental results verified that the proposed algorithm can accurately detect the shipwreck target based on residual contour information, meanwhile with an acceptable timeliness for large size sonar image data. <\/jats:p>","DOI":"10.1142\/s0218001421500063","type":"journal-article","created":{"date-parts":[[2020,6,29]],"date-time":"2020-06-29T07:21:11Z","timestamp":1593415271000},"page":"2150006","source":"Crossref","is-referenced-by-count":3,"title":["Detection Algorithm of the Shipwreck Target Based on Residual Contour Information"],"prefix":"10.1142","volume":"35","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0627-0573","authenticated-orcid":false,"given":"Ke","family":"Li","sequence":"first","affiliation":[{"name":"Electronic Engineering Institute, Naval University of Engineering, Jiefang Road 717, 145 mailbox Wuhan 430033, Hubei, P. R. China"}]},{"given":"Zhong","family":"Liu","sequence":"additional","affiliation":[{"name":"Weapon Engineering Institute, Naval University of Engineering, Wuhan, Hubei, P. R. China"}]},{"given":"Jianbin","family":"Lu","sequence":"additional","affiliation":[{"name":"Electronic Engineering Institute, Naval University of Engineering, Wuhan, Hubei, P. R. China"}]},{"given":"Liguo","family":"Liu","sequence":"additional","affiliation":[{"name":"Electronic Engineering Institute, Naval University of Engineering, Wuhan, Hubei, P. R. China"}]},{"given":"Nan","family":"Qin","sequence":"additional","affiliation":[{"name":"Naval Submarine Academy, Qingdao, Shandong, P. R. China"}]},{"given":"Jingxin","family":"An","sequence":"additional","affiliation":[{"name":"Beijing Bureau of Naval General Armaments Department, Beijing, P. R. 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