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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

  • Received: 1 December 2005
  • Accepted: 28 August 2006
  • Published:


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.


  • Quantum Information
  • Segmentation Method
  • Error Detection
  • Fuzzy Modeling
  • Potential Error

Authors’ Affiliations

Telecom, Signal, and Image Department, Institut Supérieur d’Electronique de Paris (ISEP), 21 Rue d'Assas, Paris, 75006, France
Signal and Image Processing Department, ENST, CNRS UMR 5141, 46 Rue Barrault, Paris Cedex 13, 75634, France


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© F. Rossant and I. Bloch. 2007

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