TY - GEN
T1 - Staff line detection and removal with stable paths
AU - Capela, Artur
AU - Rebelo, Ana
AU - Cardoso, Jaime S.
AU - Guedes, Carlos
PY - 2008
Y1 - 2008
N2 - Many music works produced in the past are currently available only as original manuscripts or as photocopies. Preserving them entails their digitalization and consequent accessibility in a machine-readable format, which encourages browsing, retrieval, search and analysis while providing a generalized access to the digital material. Carrying this task manually is very time consuming and error prone. While optical music recognition (OMR) systems usually perform well on printed scores, the processing of handwritten music by computers remains below the expectations. One of the fundamental stages to carry out this task is the detection and subsequent removal of staff lines. In this paper we integrate a general-purpose, knowledge-free method for the automatic detection of staff lines based on stable paths, into a recently developed staff line removal toolkit. Lines affected by curvature, discontinuities, and inclination are robustly detected. We have also developed a staff removal algorithm adapting an existing line removal approach to use the stable path algorithm at the detection stage. Experimental results show that the proposed technique outperforms well-established algorithms. The developed algorithm will now be integrated in a web based system providing seamless access to browsing, retrieval, search and analysis of submitted scores.
AB - Many music works produced in the past are currently available only as original manuscripts or as photocopies. Preserving them entails their digitalization and consequent accessibility in a machine-readable format, which encourages browsing, retrieval, search and analysis while providing a generalized access to the digital material. Carrying this task manually is very time consuming and error prone. While optical music recognition (OMR) systems usually perform well on printed scores, the processing of handwritten music by computers remains below the expectations. One of the fundamental stages to carry out this task is the detection and subsequent removal of staff lines. In this paper we integrate a general-purpose, knowledge-free method for the automatic detection of staff lines based on stable paths, into a recently developed staff line removal toolkit. Lines affected by curvature, discontinuities, and inclination are robustly detected. We have also developed a staff removal algorithm adapting an existing line removal approach to use the stable path algorithm at the detection stage. Experimental results show that the proposed technique outperforms well-established algorithms. The developed algorithm will now be integrated in a web based system providing seamless access to browsing, retrieval, search and analysis of submitted scores.
KW - Document image processing
KW - Image analysis
KW - Music
KW - Optical character recognition
UR - http://www.scopus.com/inward/record.url?scp=55849086949&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=55849086949&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:55849086949
SN - 9789898111609
T3 - SIGMAP 2008 - Proceedings of the International Conference on Signal Processing and Multimedia Applications
SP - 263
EP - 270
BT - SIGMAP 2008 - Proceedings of the International Conference on Signal Processing and Multimedia Applications
T2 - SIGMAP 2008 - International Conference on Signal Processing and Multimedia Applications
Y2 - 26 July 2008 through 29 July 2008
ER -