Using Bags of Symbols for Automatic Indexing of Graphical Document Image Databases
Author(s) -
Eugen Barbu,
Pierre Héroux,
Sébastien Adam,
Éric Trupin
Publication year - 2006
Publication title -
lecture notes in computer science
Language(s) - English
Resource type - Book series
SCImago Journal Rank - 0.249
H-Index - 400
eISSN - 1611-3349
pISSN - 0302-9743
ISBN - 3-540-34711-9
DOI - 10.1007/11767978_18
Subject(s) - computer science , search engine indexing , information retrieval , set (abstract data type) , annotation , database , automatic indexing , image retrieval , database index , data mining , image (mathematics) , artificial intelligence , programming language
International audienceA database is only usefull if it is associated a set of procedures allowing to retrieve relevant elements for the users' needs. A lot of IR techniques have been developed for automatic indexing and retrieval in document databases. Most of these use indexes depending on the textual content of documents, and very few are able to handle graphical or image content without human annotation. This paper describes an approach similar to the bag of words technique for automatic indexing of graphical document image databases and different ways to consequently query these databases. In an unsupervised manner, this approach proposes a set of automatically discovered symbols that can be combined with logical operators to build queries
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