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|Title:||Interactive collection of training samples from the Max-Tree structure|
|Authors:||OUZOUNIS GEORGIOS; GUEGUEN 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)|
|JRC Publication N°:||JRC63185|
|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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