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International Workshop on Machine Learning and Data Mining in Pattern Recognition

MLDM 1999: Machine Learning and Data Mining in Pattern Recognition pp 174–179Cite as

Recognition of Printed Music Score

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1715))

Abstract

This article describes our implementation of the Optical Music Recognition System (OMR). The system implemented in our project is based on the binary neural network ADAM. ADAM has been used for recognition of music symbols. Preprocessing was implemented by conventional techniques. We decomposed the OMR process into several phases. The results of these phases are summarized.

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References

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Faculty of Electrical Engineering, Czech Technical University, Karlovo namesti 13, 121 35, Praha 2, Czech Republic

    Tomáš Beran & Tomáš Macek

Authors
  1. Tomáš Beran
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  2. Tomáš Macek
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Editor information

Editors and Affiliations

  1. Institut für Bildverarbeitung und angewandte Informatik, Arno-Nitzsche-Str. 45, D-04277, Leipzig, Germany

    Petra Perner

  2. School of Electronic Engineering, Information Technology and Mathematics, University of Surrey, Guilford, GU2 5XH, UK

    Maria Petrou

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© 1999 Springer-Verlag Berlin Heidelberg

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Beran, T., Macek, T. (1999). Recognition of Printed Music Score. In: Perner, P., Petrou, M. (eds) Machine Learning and Data Mining in Pattern Recognition. MLDM 1999. Lecture Notes in Computer Science(), vol 1715. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48097-8_14

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  • DOI: https://doi.org/10.1007/3-540-48097-8_14

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-66599-1

  • Online ISBN: 978-3-540-48097-6

  • eBook Packages: Springer Book Archive

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