Optical Music Recognition

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2016
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Swarthmore College. Dept. of Engineering
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Thesis (B.A.)
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Full copyright to this work is retained by the student author. It may only be used for non-commercial, research, and educational purposes. All other uses are restricted.
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Abstract
In an age where computing power is cheaper than ever and memory is abundantly available, many forms of media are being converted to digital formats so they can be preserved, edited, shared, and explored more easily than ever. Sheet music for musical scores is no exception. Just as there is a need for OCR systems to scan old books into digital formats, there is a need to digitize sheet music. Some may be musicians who want to edit an old scan to correct a mistake or transpose a part. Perhaps there are historians who would like an automated system to help them preserve large corpora of old sheet music, or perform some sort of computerized analyses on them. In this paper I describe how an Optical Music Recognition (OMR) system can be constructed, and detail some of the challenges I faced in attempting to do so. In section 2 I describe the findings of Bainbridge and Bell in their review of many OMR systems, and outline the approach I intend to take. In sections 3, 4, 5, 6, 7, 8, and 9, I describe technical details of the processing pipeline I have implemented. Section 10 demonstrates t he results of my system, and section 11 concludes with a description of possible future work.
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