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Fuzzy-Shape Grammars for Cursive Script Recognition

Marc Parizeau and Réjean Plamondon

Abstract - This paper presents a new approach for cursive script segmentation and recognition, based on intrinsic models of cursive letters (allographs). The models are built using stratified context-free shape grammars that permit the definition of both syntactic and semantic attributes. These attributes synthetize pertinent morphological characteristics of allographs that are then used for recognition. The main topic of this paper concerns the parsing process developed for allograph segmentation, which uses fuzzy-logic to evaluate the likelihood of segmentation hypotheses. This process is the first step of the recognition method and leeds to the construction of a graph where nodes represent segmented allographs and arcs link adjacent nodes. The analysis of this segmentation graph can be carried out for submitting possible letter sequences to higher linguistic evaluation modules. Preliminary results are given for multi-writer isolated cursive letters. For a test database containing cursive samples of 10 different writers, an average recognition rate of 91.7% is obtained. Recognition is non personalyzed, that is, cursive samples of all writers are treated with the same algorithm parameters.

Bibtex:

@incollection{Parizeau63,
author    = { Marc Parizeau and Réjean Plamondon },
title     = { Fuzzy-Shape Grammars for Cursive Script Recognition },
booktitle = { Advances in Structural and Syntactic Pattern Recognition },
editor    = { H. Bunke },
pages     = { 320-332 },
publisher = { World Scientific Publishing },
year      = { 1993 }
}

Last modification: 2002/06/14 by parizeau

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