Abstract
In this paper a methodology for automatic accuracy evaluation in optical music recognition (OMR) applications is proposed. Presented approach assumes using ground truth images together with digital music scores describing their content. The automatic evaluation algorithm measures differences between the tested score and the reference one, both stored in MusicXML format. Some preliminary test results of this approach are presented based on the algorithm’s implementation in OMR Guido application.
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References
Blostein, D., Haken, L.: Using Diagram Generation Software to Improve Diagram Recognition: A Case Study of Music Notation. IEEE Trans. on Pattern Analysis and Machine Intelligence 21(11), 1121–1135 (1999)
Blostein, D., Baird, H.S.: A Critical Survey of Music Image Analysis, Structured Document Analysis, pp. 405–434. Springer, Heidelberg (1992)
Byrd, D., Shindele, M.: Prospects for Improving OMR with Multiple Recognizers. In: ISMIR 2006, 7th International Conference on Music Information Retrieval (2006)
Ng, K., et al.: Coding Images of Music Sheets DE4.7.1, http://www.interactivemusicnetwork.org
Bellini, P., Bruni, I., Nesi, P.: Assessing Optical Music Recognition Tools. Comput. Music J. 31(1), 68–93 (2007)
Szwoch, M.: Guido: a Musical Score Recognition System. In: ICDAR 2007: Ninth International Conf. on Document Analysis and Recognition, vol. 2. IEEE Computer Society, Los Alamitos (2007)
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Szwoch, M. (2008). Using MusicXML to Evaluate Accuracy of OMR Systems. In: Stapleton, G., Howse, J., Lee, J. (eds) Diagrammatic Representation and Inference. Diagrams 2008. Lecture Notes in Computer Science(), vol 5223. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87730-1_53
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DOI: https://doi.org/10.1007/978-3-540-87730-1_53
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-87729-5
Online ISBN: 978-3-540-87730-1
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