• Title/Summary/Keyword: 선박위치 클러스터링

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A Study on Near-miss Incidents from Maritime Traffic Flow by Clustering Vessel Positions (선박위치 클러스터링을 활용한 해상교통 근접사고 산출에 관한 연구)

  • Kim, Kwang-Il;Jeong, Jung Sik;Park, Gyei-Kark
    • Journal of the Korean Institute of Intelligent Systems
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    • v.24 no.6
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    • pp.603-608
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    • 2014
  • In the maritime traffic environment, the near-miss between vessels is the situation approaching on collision course but collision accident is not occurred. In this study, in order to calculate the near-miss between navigating vessels, the discriminating equation using ship bumper theory and vessel position clustering methods are proposed. Applying proposed module to the vessel trajectories of the WANDO waterway, we assessment navigational risk factors of vessel type, navigational speed, meeting situation.

Study on the Ship Detection Method Using SAR Imagery (SAR 영상을 이용한 선박탐지에 관한 연구)

  • Kwon, Seung-Joon;Shin, Sung-Woong
    • Journal of Korean Society for Geospatial Information Science
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    • v.17 no.1
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    • pp.131-139
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    • 2009
  • The existing vessel monitoring system using the ground surveillance radar has a difficulty in monitoring ships continuously due to the limited range of detecting ships. For resolving this problem, we carry out a research on ship detection which is to be the core technology of vessel monitoring system for ocean monitoring using SAR imagery. There are two different methods of detecting ships in SAR imagery: detection of the ship target itself and detection of the ship wake. In this paper, we mainly focus on algorithms which detect the ship itself, and also present the accuracy test after extracting positional and directional figures of the ships. After rectifying input SAR imagery using polynomial transformation, we use Wiener filter to remove speckle noises. A labeling technique and morphological filtering in conjunction with Otsu's method are used to automatically detect the ships based on the image processing domain. For ground truth data, information from a radar system is used, which allows assessing the accuracy of the proposed method. The results show that the proposed method has the high potential in automatically detecting the ships and its positional/directional figures in a fast way.

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