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Nautical Scene Segmentation Using Variable Size Image Windows and Feature Space Reclustering

  • P. Voles
  • A. A. W. Smith
  • M. K. Teal
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1843)

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.

Keywords

Feature Vector Feature Space Mahalanobis Distance Main Cluster Rigid Object 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • P. Voles
    • 1
  • A. A. W. Smith
    • 1
  • M. K. Teal
    • 1
  1. 1.Machine Vision GroupBournemouth UniversityUK

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