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Traffic pattern detection using the Hough transformation for anomaly detection to improve maritime domain awareness

机译:使用霍夫变换进行交通模式检测以进行异常检测以提高海域意识

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Techniques for extracting traffic patterns from ship position data to generate atlases of expected ocean travel are developed in this paper. An archive of historical data is used to develop a traffic density grid. The Hough transformation is used to extract linear patterns of elevated density from the traffic density grid, which can be considered the ??highways?? of the oceans. These highways collectively create an atlas that is used to define geographical regions of expected ship locations. The atlas generation techniques are demonstrated using automated information system (AIS) ship position data to detect highways in both open-ocean and coastal areas. Additionally, the atlas generation techniques are used to explore variability in ship traffic as a result of extreme weather. The development of an automatic atlas generation technique that can be used to develop a definition of normal maritime behavior is a significant result of this research.
机译:本文研究了从船舶位置数据中提取交通模式以生成预期海上航行图集的技术。历史数据档案可用于开发交通密度网格。 Hough变换用于从交通密度网格中提取密度较高的线性模式,可以将其视为“高速公路”。海洋。这些高速公路共同创建了一个地图集,用于定义预期船舶位置的地理区域。使用自动信息系统(AIS)的船舶位置数据演示地图集生成技术,以检测开放性海洋和沿海地区的高速公路。此外,图集生成技术还用于探索由于极端天气而导致的船舶交通变化。这项自动图集生成技术的发展可用于制定正常的海上行为定义,是这项研究的重要成果。

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