A platform for storing, visualizing, and interpreting collections of noisy documents
AND '10 Proceedings of the fourth workshop on Analytics for noisy unstructured text data
Unified pairwise spatial relations: an application to graphical symbol retrieval
GREC'09 Proceedings of the 8th international conference on Graphics recognition: achievements, challenges, and evolution
Symbol recognition using spatial relations
Pattern Recognition Letters
Spatio-structural symbol description with statistical feature add-on
GREC'11 Proceedings of the 9th international conference on Graphics Recognition: new trends and challenges
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In this paper, we make an attempt to use Inductive Logic Programming (ILP) to automatically learn non trivial descriptions of symbols, based on a formal description. This work is a first step in this direction and is rather a proof of concept, rather than a fully operational and robust framework.The overall goal of our approach is to express graphic symbols by a number of primitives that may be of any complexity (i.e. not necessarily just lines or points) and connecting relationships that can be deduced from straightforward state-of-the art image treatment and analysis tools. This representation is then used as an input to an ILP solver, in order to deduce non obvious characteristics that may lead to a more semantic related recognition process.