The article study the possibility of using computer vision elements for ice navigation with the aim to automate the search of “tracks” in ice. Several possible solutions are offered. Specifically, the work of the Canny algorithm, the Sobel operator, the Hough boundary detector, and the use of semantic image segmentation and neural networks deep learning are analyzed for stable detection of "tracks" in the current scene. A conceptual example of the system with three automatic optical meters to apply on Arc7 LNG is given.
computer vision, arctic navigation, automation of navigation, Sobel operator, Canny algorithm, Hough boundary detector, semantic features, deep learning, neural networks, automatic optical meter, tracks in ice, LNG carrier, Arc7 gas carrier
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