DocumentCode :
3020758
Title :
Relational learning techniques for document image understanding: comparing statistical and logical approaches
Author :
Ceci, Michelangelo ; Berardi, Margherita ; Malerba, Donato
Author_Institution :
Dipt. di Informatica, Bari Univ., Italy
fYear :
2005
fDate :
29 Aug.-1 Sept. 2005
Firstpage :
473
Abstract :
In this paper, we evaluate and systematically compare two different (multi-)relational learning methods based on a statistical approach and a logical approach for the task of document image understanding. For a fair comparison, both methods are tested on the same real world dataset consisting of multipage articles published in an international journal. An analysis of pros and cons of both approaches is reported.
Keywords :
Radon transforms; document image processing; learning (artificial intelligence); statistical analysis; Radon transform; cursive word slant correction; cursive work skew correction; document image understanding; logical approach; relational learning techniques; statistical approach; Data mining; Decision trees; Image analysis; Image recognition; Information retrieval; Layout; Learning systems; Text analysis; Tree graphs; XML;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Document Analysis and Recognition, 2005. Proceedings. Eighth International Conference on
ISSN :
1520-5263
Print_ISBN :
0-7695-2420-6
Type :
conf
DOI :
10.1109/ICDAR.2005.201
Filename :
1575591
Link To Document :
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