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dc.contributor.authorBainbridge, David
dc.contributor.authorInglis, Stuart J.
dc.date.accessioned2008-10-22T02:45:13Z
dc.date.available2008-10-22T02:45:13Z
dc.date.issued1997-11
dc.identifier.citationBainbridge, D. & Inglis, S. (1997). Musical image compression. (Working paper 97/25). Hamilton, New Zealand: University of Waikato, Department of Computer Science.en_US
dc.identifier.issn1170-487X
dc.identifier.urihttps://hdl.handle.net/10289/1121
dc.description.abstractOptical music recognition aims to convert the vast repositories of sheet music in the world into an on-line digital format [Bai97]. In the near future it will be possible to assimilate music into digital libraries and users will be able to perform searches based on a sung melody in addition to typical text-based searching [MSW+96]. An important requirement for such a system is the ability to reproduce the original score as accurately as possible. Due to the huge amount of sheet music available, the efficient storage of musical images is an important topic of study. This paper investigates whether the “knowledge” extracted from the optical music recognition (OMR) process can be exploited to gain higher compression than the JBIG international standard for bi-level image compression. We present a hybrid approach where the primitive shapes of music extracted by the optical music recognition process-note heads, note stems, staff lines and so forth-are fed into a graphical symbol based compression scheme originally designed for images containing mainly printed text. Using this hybrid approach the average compression rate for a single page is improved by 3.5% over JBIG. When multiple pages with similar typography are processed in sequence, the file size is decreased by 4-8%. Section 2 presents the relevant background to both optical music recognition and textual image compression. Section 3 describes the experiments performed on 66 test images, outlining the combinations of parameters that were examined to give the best results. The initial results and refinements are presented in Section 4, and we conclude in the last section by summarizing the findings of this work.en_US
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.publisherComputer Science, University of Waikatoen_NZ
dc.relation.ispartofseriesComputer Science Working Papers
dc.subjectcomputer scienceen_US
dc.titleMusical image compressionen_US
dc.typeWorking Paperen_US
uow.relation.series97/25
pubs.elements-id54721
pubs.place-of-publicationHamiltonen_NZ


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