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  • Research Article
  • Open Access

Robust and Adaptive OMR System Including Fuzzy Modeling, Fusion of Musical Rules, and Possible Error Detection

EURASIP Journal on Advances in Signal Processing20062007:081541

https://doi.org/10.1155/2007/81541

Received: 1 December 2005

Accepted: 28 August 2006

Published: 26 December 2006

Abstract

This paper describes a system for optical music recognition (OMR) in case of monophonic typeset scores. After clarifying the difficulties specific to this domain, we propose appropriate solutions at both image analysis level and high-level interpretation. Thus, a recognition and segmentation method is designed, that allows dealing with common printing defects and numerous symbol interconnections. Then, musical rules are modeled and integrated, in order to make a consistent decision. This high-level interpretation step relies on the fuzzy sets and possibility framework, since it allows dealing with symbol variability, flexibility, and imprecision of music rules, and merging all these heterogeneous pieces of information. Other innovative features are the indication of potential errors and the possibility of applying learning procedures, in order to gain in robustness. Experiments conducted on a large data base show that the proposed method constitutes an interesting contribution to OMR.

Keywords

Quantum InformationSegmentation MethodError DetectionFuzzy ModelingPotential Error

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Authors’ Affiliations

(1)
Telecom, Signal, and Image Department, Institut Supérieur d’Electronique de Paris (ISEP), Paris, France
(2)
Signal and Image Processing Department, ENST, CNRS UMR 5141, Paris Cedex 13, France

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Copyright

© F. Rossant and I. Bloch. 2007

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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