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A Symbol Classifier Able to Reject Wrong Shapes for Document Recognition Systems

Identifieur interne : 001E02 ( Main/Exploration ); précédent : 001E01; suivant : 001E03

A Symbol Classifier Able to Reject Wrong Shapes for Document Recognition Systems

Auteurs : Éric Anquetil [France] ; Bertrand Coüasnon [France] ; Frédéric Dambreville [France]

Source :

RBID : ISTEX:8D8E31D35E043BBBA0C3093F36DDC08D80E0248D

Abstract

Abstract: We propose in this paper a new framework to develop a transparent classifier able to deal with reject notions. The generated classifier can be characterized by a strong reliability without loosing good properties in generalization. We show on a musical scores recognition system that this classifier is very well suited to develop a complete document recognition system. Indeed this classifier allows them firstly to extract known symbols in a document (text for example) and secondly to validate segmentation hypotheses. Tests had been successfully performed on musical and digit symbols databases.

Url:
DOI: 10.1007/3-540-40953-X_17


Affiliations:


Links toward previous steps (curation, corpus...)


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