We present a document analysis system able
to assign logical labels and extract the reading order in
a broad set of documents. All information sources, from
geometric features and spatial relations to the textual
features and content are employed in the analysis. To
deal effectively with these information sources, we define
a document representation general and flexible enough
to represent complex documents. To handle such a broad
document class, it uses generic document knowledge only,
which is identified explicitly. The proposed system integrates
components based on computer vision, artificial
intelligence, and natural language processing techniques.
The system is fully implemented and experimental results
on heterogeneous collections of documents for each
component and for the entire system are presented.
@Article{AielloIJDAR2002,
author = "Aiello, M. and Monz, C. and Todoran, L. and Worring, M.",
title = "Document Understanding for a Broad Class of Documents",
journal = "International Journal on Document Analysis and Recognition",
number = "1",
volume = "5",
pages = "1--16",
year = "2002",
url = "https://ivi.fnwi.uva.nl/isis/publications/2002/AielloIJDAR2002",
pdf = "https://ivi.fnwi.uva.nl/isis/publications/2002/AielloIJDAR2002/AielloIJDAR2002.pdf"
}