—A new statistical approach based on global typographical features is proposed to the widely neglected problem of font recognition. It aims at the identification of the typeface, weight, slope and size of the text from an image block without any knowledge of the content of that text. The recognition is based on a multivariate Bayesian classifier and… (More)
SUMMARY This paper presents a statistical approach for font attribute recognition based on features extracted from projection profiles of text lines and using a Bayesian classifier. The presented features allow the discrimination of the font weight, slope and size.
In the context of a new project around structured document recognition, we address the problem of designing a software architecture which is able to integrate all the necessary, but heterogeneous know-how. Starting from the new needs brought by the CIDRE project, we propose a concrete framework built upon existing software pieces, and following the… (More)
Assisted document recognition systems have to integrate automatic recognition, manual edition and incremental learning in a single interactive environment. This paper raises the question of the organization of these three kinds of operations. When an analyzer has the ability to improve with use, there is a tradeoff between the benefits of enhancing the… (More)