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Optical Music Recognition on Windows Phone 7

  • Conference paper
The 9th International Conference on Computing and InformationTechnology (IC2IT2013)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 209))

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Abstract

Optical Music Recognition (OMR) software currently in the market are not normally designed for music learning and ad hoc interpretation; they usually require scanned input of music scores to perform well. In our work, we aimed to remove this inconvenience by using photos captured by mobile phone’s camera as the input. With the cloud-based architecture and the design without the assumption of perfect image orientation and lighting condition, we were able to eliminate many of the software’s architectural and algorithmic problems while still maintaining an overall decent performance.

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Author information

Authors and Affiliations

  1. Computer Science Program, School of Information Technology, King Mongkut’s University of Technology Thonburi, Bangkok, Thailand

    Thanachai Soontornwutikul, Nutcha Thananart, Aphinun Wantanareeyachart, Chakarida Nukoolkit & Chonlameth Arpnikanondt

Authors
  1. Thanachai Soontornwutikul
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  2. Nutcha Thananart
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  3. Aphinun Wantanareeyachart
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  4. Chakarida Nukoolkit
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  5. Chonlameth Arpnikanondt
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Corresponding author

Correspondence to Thanachai Soontornwutikul .

Editor information

Editors and Affiliations

  1. Technology North Bangkok, Faculty of Information Technology, King Mongkut's University of, 1518 Pracharat 1 Wongsawang, Bangsue, Bangkok, 10800, Thailand

    Phayung Meesad

  2. , Lehrgebiet Kommunikationsnetze, FernUniversität in Hagen, Universitätsstr. 27, Hagen, 58084, Germany

    Herwig Unger

  3. Technology North Bangkok, Faculty of Information Technology, King Mongkut's University of, 1518 Pracharat 1 Wongsawang, Bangsue, Bangkok, 10800, Thailand

    Sirapat Boonkrong

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© 2013 Springer-Verlag Berlin Heidelberg

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Soontornwutikul, T., Thananart, N., Wantanareeyachart, A., Nukoolkit, C., Arpnikanondt, C. (2013). Optical Music Recognition on Windows Phone 7. In: Meesad, P., Unger, H., Boonkrong, S. (eds) The 9th International Conference on Computing and InformationTechnology (IC2IT2013). Advances in Intelligent Systems and Computing, vol 209. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37371-8_27

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  • DOI: https://doi.org/10.1007/978-3-642-37371-8_27

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-37370-1

  • Online ISBN: 978-3-642-37371-8

  • eBook Packages: EngineeringEngineering (R0)

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