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. © 2012 Springer-Verlag.
CITATION STYLE
Gallego-Sánchez, A. J., Calera-Rubio, J., & López, D. (2012). Structural graph extraction from images. In Advances in Intelligent and Soft Computing (Vol. 151 AISC, pp. 717–724). https://doi.org/10.1007/978-3-642-28765-7_86
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