A shortest path approach for staff line detection
Main Author: | |
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Publication Date: | 2007 |
Other Authors: | , , , |
Language: | eng |
Source: | Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
Download full: | http://hdl.handle.net/11328/2491 https://doi.org/10.1109/AXMEDIS.2007.16 |
Summary: | Many music works produced in the past still exist only as original manuscripts or as photocopies. Preserving them entails their digitalization and consequent accessibility in a digital format easy-to-manage. The manual process to carry out this task is very time consuming and error prone. Optical music recognition (OMR) is a form of structured document image analysis where music symbols are isolated and identified so that the music can be conveniently processed. While OMR systems perform well on printed scores, current methods for reading handwritten musical scores by computers remain far from ideal. One of the fundamental stages of this process is the staff line detection. In this paper a new method for the automatic detection of mu- sic stave lines based on a shortest path approach is presented. Lines with some curvature, discontinuities, and inclination are robustly detected. The proposed algorithm behaves favourably when compared experimentally with well established algorithms. |
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A shortest path approach for staff line detectionMany music works produced in the past still exist only as original manuscripts or as photocopies. Preserving them entails their digitalization and consequent accessibility in a digital format easy-to-manage. The manual process to carry out this task is very time consuming and error prone. Optical music recognition (OMR) is a form of structured document image analysis where music symbols are isolated and identified so that the music can be conveniently processed. While OMR systems perform well on printed scores, current methods for reading handwritten musical scores by computers remain far from ideal. One of the fundamental stages of this process is the staff line detection. In this paper a new method for the automatic detection of mu- sic stave lines based on a shortest path approach is presented. Lines with some curvature, discontinuities, and inclination are robustly detected. The proposed algorithm behaves favourably when compared experimentally with well established algorithms.IEEE2018-12-20T17:36:41Z2018-12-202007-01-01T00:00:00Zconference objectinfo:eu-repo/semantics/publishedVersionapplication/pdfRebelo, A., Capela, A., Costa, J. F. P., Guedes, C., Carrapatoso, E., & Cardoso, J. S. (2007). A shortest path approach for staff line detection. In Third International Conference on Automated Production of Cross Media Content for Multi-Channel Distribution (AxMEDIS 2007), Barcelona, Spain, 28-30 Nov.2007 (pp. 79-85). Disponível no Repositório UPT, http://hdl.handle.net/11328/2491http://hdl.handle.net/11328/2491Rebelo, A., Capela, A., Costa, J. F. P., Guedes, C., Carrapatoso, E., & Cardoso, J. S. (2007). A shortest path approach for staff line detection. In Third International Conference on Automated Production of Cross Media Content for Multi-Channel Distribution (AxMEDIS 2007), Barcelona, Spain, 28-30 Nov.2007 (pp. 79-85). Disponível no Repositório UPT, http://hdl.handle.net/11328/2491http://hdl.handle.net/11328/2491https://doi.org/10.1109/AXMEDIS.2007.16enghttps://ieeexplore.ieee.org/document/4402863http://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessRebelo, AnaCapelo, ArturCosta, Joaquim F. PintoGuedes, CarlosCarrapatoso, Euricoreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-01-09T02:17:31Zoai:repositorio.upt.pt:11328/2491Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T19:34:07.393739Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse |
dc.title.none.fl_str_mv |
A shortest path approach for staff line detection |
title |
A shortest path approach for staff line detection |
spellingShingle |
A shortest path approach for staff line detection Rebelo, Ana |
title_short |
A shortest path approach for staff line detection |
title_full |
A shortest path approach for staff line detection |
title_fullStr |
A shortest path approach for staff line detection |
title_full_unstemmed |
A shortest path approach for staff line detection |
title_sort |
A shortest path approach for staff line detection |
author |
Rebelo, Ana |
author_facet |
Rebelo, Ana Capelo, Artur Costa, Joaquim F. Pinto Guedes, Carlos Carrapatoso, Eurico |
author_role |
author |
author2 |
Capelo, Artur Costa, Joaquim F. Pinto Guedes, Carlos Carrapatoso, Eurico |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Rebelo, Ana Capelo, Artur Costa, Joaquim F. Pinto Guedes, Carlos Carrapatoso, Eurico |
description |
Many music works produced in the past still exist only as original manuscripts or as photocopies. Preserving them entails their digitalization and consequent accessibility in a digital format easy-to-manage. The manual process to carry out this task is very time consuming and error prone. Optical music recognition (OMR) is a form of structured document image analysis where music symbols are isolated and identified so that the music can be conveniently processed. While OMR systems perform well on printed scores, current methods for reading handwritten musical scores by computers remain far from ideal. One of the fundamental stages of this process is the staff line detection. In this paper a new method for the automatic detection of mu- sic stave lines based on a shortest path approach is presented. Lines with some curvature, discontinuities, and inclination are robustly detected. The proposed algorithm behaves favourably when compared experimentally with well established algorithms. |
publishDate |
2007 |
dc.date.none.fl_str_mv |
2007-01-01T00:00:00Z 2018-12-20T17:36:41Z 2018-12-20 |
dc.type.driver.fl_str_mv |
conference object |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
Rebelo, A., Capela, A., Costa, J. F. P., Guedes, C., Carrapatoso, E., & Cardoso, J. S. (2007). A shortest path approach for staff line detection. In Third International Conference on Automated Production of Cross Media Content for Multi-Channel Distribution (AxMEDIS 2007), Barcelona, Spain, 28-30 Nov.2007 (pp. 79-85). Disponível no Repositório UPT, http://hdl.handle.net/11328/2491 http://hdl.handle.net/11328/2491 Rebelo, A., Capela, A., Costa, J. F. P., Guedes, C., Carrapatoso, E., & Cardoso, J. S. (2007). A shortest path approach for staff line detection. In Third International Conference on Automated Production of Cross Media Content for Multi-Channel Distribution (AxMEDIS 2007), Barcelona, Spain, 28-30 Nov.2007 (pp. 79-85). Disponível no Repositório UPT, http://hdl.handle.net/11328/2491 http://hdl.handle.net/11328/2491 https://doi.org/10.1109/AXMEDIS.2007.16 |
identifier_str_mv |
Rebelo, A., Capela, A., Costa, J. F. P., Guedes, C., Carrapatoso, E., & Cardoso, J. S. (2007). A shortest path approach for staff line detection. In Third International Conference on Automated Production of Cross Media Content for Multi-Channel Distribution (AxMEDIS 2007), Barcelona, Spain, 28-30 Nov.2007 (pp. 79-85). Disponível no Repositório UPT, http://hdl.handle.net/11328/2491 |
url |
http://hdl.handle.net/11328/2491 https://doi.org/10.1109/AXMEDIS.2007.16 |
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eng |
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eng |
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IEEE |
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IEEE |
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