Abstract
This paper describes the development of a system for the segmentation of small vessels and objects present in a maritime environment. The system assumes no a priori knowledge of the sea, but uses statistical analysis within variable size image windows to determine a characteristic vector that represents the current sea state. A space of characteristic vectors is searched and a main group of characteristic vectors and its centroid found automatically by using a new method of iterative reclustering. This method is an extension and improvement of the work described in [9]. A Mahalanobis distance measure from the centroid is calculated for each characteristic vector and is used to determine inhomogenities in the sea caused by the presence of a rigid object. The system has been tested using several input image sequences of static small objects such as buoys and small and large maritime vessels moving into and out of a harbour scene and the system successfully segmented these objects.
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Voles, P., Smith, A.A.W., Teal, M.K. (2000). Nautical Scene Segmentation Using Variable Size Image Windows and Feature Space Reclustering. In: Vernon, D. (eds) Computer Vision — ECCV 2000. ECCV 2000. Lecture Notes in Computer Science, vol 1843. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45053-X_21
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DOI: https://doi.org/10.1007/3-540-45053-X_21
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