Character Rotation Absorption Using a Dynamic Neural Network Topology: Comparison With Invariant Features

Christophe Choisy, Hubert Cecotti, Abdel Belaïd

Abstract

This paper treats on rotation absorption in neural networks for multi-oriented character recognition. Classical approaches are based on several rotation invariant features. Here, we propose to use a dynamic neural network topology to absorb the rotation phenomenon. The basic idea is to preserve as most as possible the graphical information, that contains all the information. The proposal is to dynamically modify the neural network architecture, in order to take into account the rotation variation of the analysed pattern. We use too a specific topology that carry out a polar transformation inside the network. The interest of such a transformation is to transform the rotation problem from a 2D problem to a 1D problem, that is easier to treat. These proposals are applied on a synthetic and on a real EDF1 base of multi-oriented characters. A comparison is made with Fourier and Fourier-Mellin invariants.

References

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Paper Citation


in Harvard Style

Choisy C., Cecotti H. and Belaïd A. (2004). Character Rotation Absorption Using a Dynamic Neural Network Topology: Comparison With Invariant Features . In Proceedings of the 4th International Workshop on Pattern Recognition in Information Systems - Volume 1: PRIS, (ICEIS 2004) ISBN 972-8865-01-5, pages 90-97. DOI: 10.5220/0002683500900097


in Bibtex Style

@conference{pris04,
author={Christophe Choisy and Hubert Cecotti and Abdel Belaïd},
title={Character Rotation Absorption Using a Dynamic Neural Network Topology: Comparison With Invariant Features},
booktitle={Proceedings of the 4th International Workshop on Pattern Recognition in Information Systems - Volume 1: PRIS, (ICEIS 2004)},
year={2004},
pages={90-97},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002683500900097},
isbn={972-8865-01-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 4th International Workshop on Pattern Recognition in Information Systems - Volume 1: PRIS, (ICEIS 2004)
TI - Character Rotation Absorption Using a Dynamic Neural Network Topology: Comparison With Invariant Features
SN - 972-8865-01-5
AU - Choisy C.
AU - Cecotti H.
AU - Belaïd A.
PY - 2004
SP - 90
EP - 97
DO - 10.5220/0002683500900097