Title: Interactive collection of training samples from the Max-Tree structure
Authors: OUZOUNIS GEORGIOSGUEGUEN LIONEL
Citation: Proceedings of the 2011 18th IEEE International Conference on Image Processing (ICIP) p. 1449-1452
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Publication Year: 2011
JRC N°: JRC63185
ISBN: 978-1-4577-1304-0
ISSN: 1522-4880
URI: http://publications.jrc.ec.europa.eu/repository/handle/JRC63185
DOI: 10.1109/ICIP.2011.6115714
10.1109/ICIP.2011.6115714
Type: Contributions to Conferences
Abstract: In this paper we present a fast, interactive method for collecting structural primitives from objects of interest contained within manually selected image regions. The input image is projected onto a Max-Tree and Min-Tree structure from which a pixel-to-node mapper marks the nodes of each tree that correspond to peak components explicitly contained within the selected window. In a pass through the selected nodes, an attribute vector is constructed from the pool of auxiliary data associated to each node separately. The set of all attribute vectors is mapped into a pre-computed multidimensional feature space from which a binary criterion is constructed to accept or reject the remaining image objects. The method is demonstrated in a real application on information extraction from very high resolution satellite imagery.
JRC Institute:Institute for the Protection and Security of the Citizen

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