Éditeur(s) : HAL CCSD Springer Verlag
Résumé : 17 pages, 11 figures.
International audience
The problem addressed in this paper is the automatic extraction of names from a document image. Our approach relies on the combination of two complementary analyses. First, the image-based analysis exploits visual clues to select the regions of interest in the document. Second, the textual-based analysis searches for name patterns and low-level word textual features. Both analyses are then combined at the word level through a neural network fusion scheme. Reported results on degraded documents such as facsimile and photocopied technical journals demonstrate the interest of the combined approach.
ISSN: 1433-7541

hal-00329459
https://hal.archives-ouvertes.fr/hal-00329459
DOI : 10.1007/s10044-006-0038-6

Éditeur(s) : HAL CCSD IEEE Computer Society
Résumé : 5 pages, 2 figures, composed with Microsoft Word. Proceedings of the Seventh International Conference on Document Analysis and Recognition (ICDAR 2003). Edinburgh, Écosse, 3-6 août 2003. Également disponible à l'URL : http://www.cse.salford.ac.uk/prima/ICDAR2003/Papers/0100_563_likforman_l.pdf
International audience
In the frame of a Unified Messaging System, a crucial task of the system is to provide the user with key information on every message received, like keywords reflecting the object of the message, or the name of the sender. However, in the case of facsimiles, this information is not as easy to detect as in the case of e-mails, since no standard headers are defined. The aim of the present work is to identify and extract a specific information (the name of the sender) from a fax cover page. For this purpose, methods based on image document analysis (OCR recognition, physical blocks selection), and text analysis methods (optimised dictionary lookup, local grammar rules), are implemented to work in parallel. The fusion of their results brings a more accurate guess than any of the methods would achieve separately.
Proceedings of the Seventh International Conference on Document Analysis and Recognition (ICDAR 2003)
Edinburgh, United Kingdom

hal-00328998
https://hal.archives-ouvertes.fr/hal-00328998
DOI : 10.1109/ICDAR.2003.1227724