@InProceedings{Mar{\c c}alRusi{\~n}ol2013,
author="Mar{\c{c}}al Rusi{\~n}ol
and T.Benkhelfallah
and V. Poulain d{\textquoteright}Andecy",
title="Field Extraction from Administrative Documents by Incremental Structural Templates",
booktitle="12th International Conference on Document Analysis and Recognition",
year="2013",
pages="1100--1104",
abstract="In this paper we present an incremental framework aimed at extracting field information from administrative document images in the context of a Digital Mail-room scenario. Given a single training sample in which the user has marked which fields have to be extracted from a particular document class, a document model representing structural relationships among words is built. This model is incrementally refined as the system processes more and more documents from the same class. A reformulation of the tf-idf statistic scheme allows to adjust the importance weights of the structural relationships among words. We report in the experimental section our results obtained with a large dataset of real invoices.",
optnote="DAG; 600.56; 600.045; 605.203; 602.101",
optnote="exported from refbase (http://refbase.cvc.uab.es/show.php?record=2346), last updated on Thu, 10 Nov 2016 12:12:13 +0100",
issn="1520-5363",
doi="10.1109/ICDAR.2013.223",
file=":http://refbase.cvc.uab.es/files/RBP2013.pdf:PDF"
}