@inproceedings{4adf887cfc244be3bfa85f1dc3a3e97b,
title = "Model-based graphics recognition",
abstract = "In this paper, we illustrate the use of a novel probabilistic framework for document analysis on typical problems of document layout analysis and graphics recognition. Our system uses an explicit descriptive model of the document class to find the most likely interpretation of a scanned document image. In contrast to the traditional pipeline architecture, our system carries out all stages of the analysis with a single inference engine, allowing for an end-to- end propagation of the uncertainty.",
author = "Stuckelberg, \{Marc Vuilleumier\} and David Doermann",
note = "Publisher Copyright: {\textcopyright} Springer-Verlag Berlin Heidelberg 2000.; 3rd International Workshop on Graphics Recognition, GREC 1999 ; Conference date: 26-09-1999 Through 27-09-1999",
year = "2000",
language = "English",
isbn = "3540412220",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "121--132",
editor = "Dov Dori and Chhabra, \{Atul K.\}",
booktitle = "Graphics Recognition - Recent Advances - 3rd International Workshop, GREC 1999, Selected Papers",
address = "Germany",
}