Title: Hierarchical Segmentation of Complex Structures
Authors: AKÇAY Huseyin GökhanAKSOY SelimSOILLE Pierre
Citation: Proceedings of the 20th International Conference On Pattern Recognition - ICPR 2010, ISBN: 978-0-7695-4109-9 p. 1120-1123
Publisher: IEEE Computer Society Press
Publication Year: 2010
JRC N°: JRC58977
URI: http://publications.jrc.ec.europa.eu/repository/handle/JRC58977
DOI: 10.1109/ICPR.2010.280
Type: Contributions to Conferences
Abstract: We present an unsupervised hierarchical segmentation algorithm for detection of complex heterogeneous image structures that are comprised of simpler homogeneous primitive objects. An initial segmentation step produces regions corresponding to primitive objects with uniform spectral content. Next, the transitions between neighboring regions are modeled and clustered. We assume that the clusters that are dense and large enough in this transition space can be considered as significant. Then, the neighboring regions belonging to the significant clusters are merged to obtain the next level in the hierarchy. The experiments show that the algorithm that iteratively clusters and merges region groups is able to segment high-level complex structures in a hierarchical manner
JRC Institute:Institute for the Protection and Security of the Citizen

Files in This Item:
There are no files associated with this item.


Items in repository are protected by copyright, with all rights reserved, unless otherwise indicated.