Abstract
Note symbol recognition plays a fundamental role in the process of an OMR system. In this paper, we propose new approaches for recognizing notes by extracting primitives and assembling them into constructed symbols. Firstly, we propose robust algorithms for extracting primitives (stems, noteheads and beams) based on Run-Length Encoding. Secondly, introduce the concept of interaction field to describe the relationship between primitives, and define six hierarchical categories for the structure of notes. Thirdly, propose an effective sequence to assemble the primitives into notes, guided by the mechanism of giving priority to the key structures. To evaluate the performance of those approaches,wepresent experimental results on real-life scores and comparisons with commercial systems. The results show our approaches can recognize notes with high-accuracy and powerful adaptability, especially for the complicated scores with high density of symbols.
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Liu, X. (2012). Note Symbol Recognition for Music Scores. In: Pan, JS., Chen, SM., Nguyen, N.T. (eds) Intelligent Information and Database Systems. ACIIDS 2012. Lecture Notes in Computer Science(), vol 7197. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28490-8_28
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DOI: https://doi.org/10.1007/978-3-642-28490-8_28
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-28489-2
Online ISBN: 978-3-642-28490-8
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