{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,11]],"date-time":"2025-12-11T21:02:21Z","timestamp":1765486941695,"version":"build-2065373602"},"reference-count":18,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2023,6,30]],"date-time":"2023-06-30T00:00:00Z","timestamp":1688083200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100006162","name":"Funda\u00e7\u00e3o de Amparo \u00e0 Ci\u00eancia e Tecnologia de Pernambuco (FACEPE)","doi-asserted-by":"publisher","award":["APQ-0356-1.03\/21","APQ-0072-1.03\/22"],"award-info":[{"award-number":["APQ-0356-1.03\/21","APQ-0072-1.03\/22"]}],"id":[{"id":"10.13039\/501100006162","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>The opportunities for leveraging technology to enhance the efficiency of vessel port activities are vast. Applying video analytics to model and optimize certain processes offers a remarkable way to improve overall operations. Within the realm of vessel port activities, two crucial processes are vessel approximation and the docking process. This work specifically focuses on developing a vessel velocity estimation model and a docking mooring analytical system using a computer vision approach. The study introduces algorithms for speed estimation and mooring bitt detection, leveraging techniques such as the Structural Similarity Index (SSIM) for precise image comparison. The obtained results highlight the effectiveness of the proposed algorithms, demonstrating satisfactory speed estimation capabilities and successful identification of tied cables on the mooring bitts. These advancements pave the way for enhanced safety and efficiency in vessel docking procedures. However, further research and improvements are necessary to address challenges related to occlusions and illumination variations and explore additional techniques to enhance the models\u2019 performance and applicability in real-world scenarios.<\/jats:p>","DOI":"10.3390\/a16070326","type":"journal-article","created":{"date-parts":[[2023,7,3]],"date-time":"2023-07-03T00:42:46Z","timestamp":1688344966000},"page":"326","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Vessel Velocity Estimation and Docking Analysis: A Computer Vision Approach"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3554-0157","authenticated-orcid":false,"given":"Jo\u00e3o V. R.","family":"de Andrade","sequence":"first","affiliation":[{"name":"Escola Polit\u00e9cnica de Pernambuco, University of Pernambuco, Recife 50720-001, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6001-3925","authenticated-orcid":false,"given":"Bruno J. T.","family":"Fernandes","sequence":"additional","affiliation":[{"name":"Escola Polit\u00e9cnica de Pernambuco, University of Pernambuco, Recife 50720-001, Brazil"}]},{"given":"Andr\u00e9 R. L. C.","family":"Iz\u00eddio","sequence":"additional","affiliation":[{"name":"Suape, Complexo Industrial Portu\u00e1rio Governador Eraldo Gueiros, Ipojuca 55590-000, Brazil"}]},{"given":"Nilson M.","family":"da Silva Filho","sequence":"additional","affiliation":[{"name":"Suape, Complexo Industrial Portu\u00e1rio Governador Eraldo Gueiros, Ipojuca 55590-000, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1131-3382","authenticated-orcid":false,"given":"Francisco","family":"Cruz","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, University of New South Wales, Sydney, NSW 2052, Australia"},{"name":"Escuela de Ingenier\u00eda, Universidad Central de Chile, Santiago 8330601, Chile"}]}],"member":"1968","published-online":{"date-parts":[[2023,6,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Olatunji, I., and Cheng, C.H. (2019). Video Analytics for Visual Surveillance and Applications: An Overview and Survey, Springer.","DOI":"10.1007\/978-3-030-15628-2_15"},{"key":"ref_2","unstructured":"Fefilatyev, S. (2012). Algorithms for Visual Maritime Surveillance with Rapidly Moving Camera, ProQuest."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Lee, H.T., Lee, J.S., Son, W.J., and Cho, I.S. (2020). Development of machine learning strategy for predicting the risk range of Ship\u2019s berthing velocity. J. Mar. Sci. Eng., 8.","DOI":"10.3390\/jmse8050376"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"7194342","DOI":"10.1155\/2020\/7194342","article-title":"Video-Based Detection Infrastructure Enhancement for Automated Ship Recognition and Behavior Analysis","volume":"2020","author":"Chen","year":"2020","journal-title":"J. Adv. 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