TY - GEN
T1 - A shortest path approach for staff line detection
AU - Rebelo, Ana
AU - Guedes, Carlos
AU - Capela, Artur
AU - Carrapatoso, Eurico
AU - Pinto Da Costa, Joaquim F.
AU - Cardoso, Jaime S.
PY - 2007
Y1 - 2007
N2 - 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 music 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.
AB - 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 music 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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U2 - 10.1109/AXMEDIS.2007.16
DO - 10.1109/AXMEDIS.2007.16
M3 - Conference contribution
AN - SCOPUS:47849092785
SN - 0769530303
SN - 9780769530307
T3 - Proceedings - 3rd International Conference on Automated Production of Cross Media Content for Multi-Channel Distribution, AXMEDIS 2007
SP - 79
EP - 85
BT - Proceedings - 3rd International Conference on Automated Production of Cross Media Content for Multi-Channel Distribution, AXMEDIS 2007
T2 - 3rd International Conference on Automated Production of Cross Media Content for Multi-Channel Distribution, AXMEDIS 2007
Y2 - 28 November 2007 through 30 November 2007
ER -