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. © Springer-Verlag Berlin Heidelberg 2005.
CITATION STYLE
Arrivault, D., Richard, N., Fernandez-Maloigne, C., & Bouyer, P. (2005). Collaboration between statistical and structural approaches for old handwritten characters recognition. In Lecture Notes in Computer Science (Vol. 3434, pp. 291–300). Springer Verlag. https://doi.org/10.1007/978-3-540-31988-7_28
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