Structural graph extraction from images

We present three new algorithms to model images with graph primitives. Our main goal is to propose algorithms that could lead to a broader use of graphs, especially in pattern recognition tasks. The first method considers the q-tree representation and the neighbourhood of regions. We also propose a method which, given any region of a q-tree, finds its neighbour regions. The second algorithm reduces the image to a structural grid. This grid is postprocessed in order to obtain a directed acyclic graph. The last method takes into account the skeleton of an image to build the graph. It is a natural generalization of similar works on trees [8, 12]. Experiments show encouraging results and prove the usefulness of the proposed models in more advanced tasks, such as syntactic pattern recognition tasks.This work is partially supported by Spanish MICINN (contract TIN2011-28260-C03-01, contract TIN2009-14205-C04-C1) and CONSOLIDER-INGENIO 2010 (contract CSD2007-00018)Gallego-Sánchez, A.; Calera Rubio, J.; López Rodríguez, D. (2012). Structural graph extraction from images. En Distributed Computing and Artificial Intelligence: 9th International Conference. Springer. 717-724. doi:10.1007/978-3-642-28765-7_86S71772