Inductive Logic Programming for Symbol Recognition

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. Th...

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Bibliographic Details
Main Authors: Santosh, K.C., Lamiroy, B., Ropers, J.-P.
Format: Conference Proceeding
Language:English
Subjects:
classification
Data mining
Electronic mail
Graphics
Image analysis
inductive logic programming
Joining processes
Logic programming
Robustness
symbol recognition
Text analysis
Vocabulary
Online Access:Request full text
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Description
Summary: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.
ISSN:1520-5363
2379-2140
DOI:10.1109/ICDAR.2009.166