Interactive collection of training samples from the Max-Tree structure

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.

OUZOUNIS Georgios;  GUEGUEN Lionel; 

2012-05-30

Institute of Electrical and Electronics Engineers (IEEE)

JRC63185

978-1-4577-1304-0,   

1522-4880,   

https://publications.jrc.ec.europa.eu/repository/handle/JRC63185,   

10.1109/ICIP.2011.6115714,