Abstract
There is a growing number of collections of readily available scanned musical documents, whether generated and managed by libraries, research projects, or volunteer efforts. They are typically digital images; for computational musicology we also need the musical data in machine-readable form. Optical Music Recognition (OMR) can be used on printed music, but is prone to error, depending on document condition and the quality of intermediate stages in the digitization process such as archival photographs. This work addresses the detection of one such error—duplication of images—and the discovery of other relationships between images in the process.
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Acknowledgements
This work was supported by the Transforming Musicology project, AHRC AH/L006820/1.
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Rhodes, C., Crawford, T., d’Inverno, M. (2016). Duplicate Detection in Facsimile Scans of Early Printed Music. In: Wilhelm, A., Kestler, H. (eds) Analysis of Large and Complex Data. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Cham. https://doi.org/10.1007/978-3-319-25226-1_38
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DOI: https://doi.org/10.1007/978-3-319-25226-1_38
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