A syntax-directed method for numerical field extraction using classifier combination.

In this paper, we introduce an alpha-numerical se- quences extraction system (keywords, numerical fields or alpha-numerical sequences) in unconstrained hand- written documents.

The a priori knowledge such as the number of digits of a researched field and the potential position of the sep- arators are merged into some text line models, for each kind of

Reject: since most of the components are outliers, the numeral and separator recognition hypotheses must be sub- mitted to an outlier rejection system which provides a con-

We now describe the components of the segmentation-driven recognition : the numeral classifier, the touching digit recognition method using a segmentation method, and the reject

The extraction of numerical data (file number, customer reference, phone number, zip code in an address, ...) in a handwritten document whose

In this paper, an innovating information extraction system is introduced, based on a text line model able to handle relevant (words of a lexicon) and irrelevant (everything

Reject: since most of the components are outliers, the numeral and separator recognition hypotheses must be sub- mitted to an outlier rejection system which provides a con-

This is performed thanks to a seg- mentation driven by recognition stage described afterwards, which provides a three-level recognition trellis with confi- dence values for