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Pattern Analysis and Applications
Published in: Pattern Analysis and Applications 4/2015

01-11-2015 | Short Paper

Avoiding staff removal stage in optical music recognition: application to scores written in white mensural notation

Authors: Jorge Calvo-Zaragoza, Isabel Barbancho, Lorenzo J. Tardón, Ana M. Barbancho

Published in: Pattern Analysis and Applications | Issue 4/2015

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Abstract

Staff detection and removal is one of the most important issues in optical music recognition (OMR) tasks since common approaches for symbol detection and classification are based on this process. Due to its complexity, staff detection and removal is often inaccurate, leading to a great number of errors in posterior stages. For this reason, a new approach that avoids this stage is proposed in this paper, which is expected to overcome these drawbacks. Our approach is put into practice in a case of study focused on scores written in white mensural notation. Symbol detection is performed by using the vertical projection of the staves. The cross-correlation operator for template matching is used at the classification stage. The goodness of our proposal is shown in an experiment in which our proposal attains an extraction rate of 96 % and a classification rate of 92 %, on average. The results found have reinforced the idea of pursuing a new research line in OMR systems without the need of the removal of staff lines.
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Metadata
Title
Avoiding staff removal stage in optical music recognition: application to scores written in white mensural notation
Authors
Jorge Calvo-Zaragoza
Isabel Barbancho
Lorenzo J. Tardón
Ana M. Barbancho
Publication date
01-11-2015
Publisher
Springer London
Published in
Pattern Analysis and Applications / Issue 4/2015
Print ISSN: 1433-7541
Electronic ISSN: 1433-755X
DOI
https://doi.org/10.1007/s10044-014-0415-5

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