Title :
Inductive Logic Programming for Symbol Recognition
Author :
Santosh, K.C. ; Lamiroy, Bart ; Ropers, Jean-Philippe
Author_Institution :
LORIA, Inria Nancy- Grand Est, Villers-les-Nancy, France
Abstract :
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.
Keywords :
image classification; image representation; inductive logic programming; object recognition; shape recognition; ILP solver; automatic learning; formal shape description; graphical symbol recognition process; image classification; image representation; inductive logic programming; operational robust framework; semantic concept; state-of-the-art image analysis tool; state-of-the-art image treatment tool; Art; Data mining; Electronic mail; Graphics; Image analysis; Joining processes; Logic programming; Robustness; Text analysis; Vocabulary; classification; inductive logic programming; symbol recognition;
Conference_Titel :
Document Analysis and Recognition, 2009. ICDAR '09. 10th International Conference on
Conference_Location :
Barcelona
Print_ISBN :
978-1-4244-4500-4
Electronic_ISBN :
1520-5363
DOI :
10.1109/ICDAR.2009.166
