This paper presents an ongoing project working on an optical handwritten music manuscript recognition system. A brief background of Optical Music Recognition (OMR) is presented, together with a discussion on some of the main obstacles in this domain. An earlier OMR prototype for printed music scores is described, with illustrations of the low-level pre-processing and segmentation routines, followed by a discussion on its limitations for handwritten manuscripts processing, which led to the development of a stroke-based segmentation approach using mathematical morphology. The pre-processing sub-systems consist of a list of automated processes, including thresholding, deskewing, basic layout analysis and general normalization parameters such as the stave line thickness and spacing. High-level domain knowledge enhancements, output format and future directions are outlined.
CITATION STYLE
Ng, K. (2002). Music manuscript tracing. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2390, pp. 330–342). Springer Verlag. https://doi.org/10.1007/3-540-45868-9_29
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