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Collaboration Between Statistical and Structural Approaches for Old Handwritten Characters Recognition

Collaboration Between Statistical and Structural Approaches for Old Handwritten Characters Recognition

5th IAPR International Workshop on Graph Based Representation in Pattern Recognition (GbR'05), Volume 3434, pages 291-300, Poitiers - Mars 2005
In this article we try to make different kinds of information cooperate in a characters recognition system addressing old Greek and Egyptians documents. We first use a statistical approach based on classical shape descriptors (Zernike, Fourier). Then we use a structural classification method with an attributed graph description of characters and a random graph modeling of classes. The hypothesis, that structural methods bring topological information that statistical methods do not, is validated on Greek characters. A cooperation with a chain of classifiers based on reject management is then proposed. Due to computation cost, the goal of such a chain is to use the structural approach only if the statistical one fails.

BibTex references

@InProceedings{ARFB2005_1505,
author = {Arrivault, D. and Richard, N. and Fernandez-Maloigne, C. and Bouyer, P.},
title = {Collaboration Between Statistical and Structural Approaches for Old Handwritten Characters Recognition.},
booktitle = {5th IAPR International Workshop on Graph Based Representation in Pattern Recognition (GbR'05)},
volume = {3434},
pages = {291-300},
month = {Mars},
year = {2005},
publisher = {Springer},
note = {Poitiers},
}