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Optical recognition of music symbols
Author(s) -
Ana Rebelo,
Artur Capela,
Jaime S. Cardoso
Publication year - 2009
Publication title -
international journal on document analysis and recognition (ijdar)
Language(s) - English
Resource type - Journals
eISSN - 1433-2833
pISSN - 1433-2825
DOI - 10.1007/s10032-009-0100-1
Subject(s) - computer science , transformation (genetics) , musical , context (archaeology) , face (sociological concept) , scheme (mathematics) , artificial intelligence , speech recognition , emphasis (telecommunications) , ideal (ethics) , natural language processing , pattern recognition (psychology) , mathematics , linguistics , visual arts , gene , mathematical analysis , paleontology , biology , epistemology , philosophy , telecommunications , biochemistry , art , chemistry
Many musical works produced in the past are still currently available only as original manuscripts or as photocopies. The preservation of these works requires their digitalization and transformation into a machine-readable format. However, and despite the many research activities on optical music recognition (OMR), the results for handwritten musical scores are far from ideal. Each of the proposed methods lays the emphasis on different properties and therefore makes it difficult to evaluate the efficiency of a proposed method. We present in this article a comparative study of several recognition algorithms of music symbols. After a review of the most common procedures used in this context, their respective performances are compared using both real and synthetic scores. The database of scores was augmented with replicas of the existing patterns, transformed according to an elastic deformation technique. Such transformations aim to introduce invariances in the prediction with respect to the known variability in the symbols, particularly relevant on handwritten works. The following study and the adopted databases can constitute a reference scheme for any researcher who wants to confront a new OMR algorithm face to well-known ones.

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