Pattern recognition: statistical, structural and neural approaches
Pattern recognition: statistical, structural and neural approaches
Machine vision
Affine analysis of image sequences
Affine analysis of image sequences
Image Processing, Analysis, and Machine Vision
Image Processing, Analysis, and Machine Vision
Maritime surveillance: Tracking ships inside a dynamic background using a fast level-set
Expert Systems with Applications: An International Journal
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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.