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Martín H., José Antonio Montero De Juan, Francisco Javier Gómez González, Daniel 2023-06-20T05:46:37Z 2023-06-20T05:46:37Z 2010 H., M.J.A., Montero, J., Yanez, J., Gomez, D.: A divisive hierarchical k-means based algorithm for image segmentation. En: 2010 IEEE International Conference on Intelligent Systems and Knowledge Engineering. pp. 300-304. IEEE, Hangzhou (2010) 978-1-4244-6791-4 10.1109/ISKE.2010.5680865 https://hdl.handle.net/20.500.14352/45547 https//doi.org/10.1109/ISKE.2010.5680865 http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=5680865&abstractAccess=no&userType=inst In this paper we present a divisive hierarchical method for the analysis and segmentation of visual images. The proposed method is based on the use of the k-means method embedded in a recursive algorithm to obtain a clustering at each node of the hierarchy. The recursive algorithm determines automatically at each node a good estimate of the parameter k (the number of clusters in the k-means algorithm) based on relevant statistics. We have made several experiments with different kinds of images obtaining encouraging results showing that the method can be used effectively not only for automatic image segmentation but also for image analysis and, even more, data mining. eng restricted access A divisive hierarchical k-means based algorithm for image segmentation book part