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AN IMPROVED K-MEANS CLUSTERING ALGORITHM FOR IMAGE SEGMENTATION

William Robson SchwartzRicardo Dutra da SilvaRodrigo MinettoHÉLIO PEDRINI

Image segmentation is a primary step in many computer vision applications, whose purposeis to extract information from the images to allow the discrimination among different objects of interest. This task usually involves the partitioning of the image into a number of clusters, such that the data in each cluster share similar features. This work describes a new clustering algorithm for providing a more suitable coarse segmentation, used for parameter estimation. Experimental results and comparisons to other techniques are presented and discussed to demonstrate the effectiveness of the proposed method.

http://www.lbd.dcc.ufmg.br/colecoes/wvc/2006/0034.pdf

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