IMAGE SEGMENTATION BY GRAVITATIONAL CLUSTERING

摘要

In segmenting multidimensional image data, the data is represented as a set of points in a vector space which is the product of the vector space of pixel values and the vector space of pixel locations. Segments are determined by the result of clustering of the points, typically by simulating gravitational clustering of the points considered as point masses. From time to time the points are merged according to a proximity criterion, typically defined by mutual occupancy of a pre-defined hypercube in the vector space. The mapping of original pixels to points is tracked during the simulation process, so that pixels may be mapped to segments.