TY - JOUR
T1 - The ICDAR/GREC 2013 music scores competition: Staff removal
AU - Fornés, Alicia
AU - Kieu, Van Cuong
AU - Visani, Muriel
AU - Journet, Nicholas
AU - Dutta, Anjan
PY - 2014/1/1
Y1 - 2014/1/1
N2 - © Springer-Verlag Berlin Heidelberg 2014. The first competition on music scores that was organized at ICDAR and GREC in 2011 awoke the interest of researchers, who participated in both staff removal and writer identification tasks. In this second edition, we focus on the staff removal task and simulate a real case scenario concerning old and degraded music scores. For this purpose, we have generated a new set of semi-synthetic images using two degradation models that we previously introduced: local noise and 3D distortions. In this extended paper we provide an extended description of the dataset, degradation models, evaluation metrics, the participant’s methods and the obtained results that could not be presented at ICDAR and GREC proceedings due to page limitations.
AB - © Springer-Verlag Berlin Heidelberg 2014. The first competition on music scores that was organized at ICDAR and GREC in 2011 awoke the interest of researchers, who participated in both staff removal and writer identification tasks. In this second edition, we focus on the staff removal task and simulate a real case scenario concerning old and degraded music scores. For this purpose, we have generated a new set of semi-synthetic images using two degradation models that we previously introduced: local noise and 3D distortions. In this extended paper we provide an extended description of the dataset, degradation models, evaluation metrics, the participant’s methods and the obtained results that could not be presented at ICDAR and GREC proceedings due to page limitations.
KW - Competition
KW - Graphics recognition
KW - Music scores
KW - Staff removal
KW - Writer identification
U2 - 10.1007/978-3-662-44854-0_16
DO - 10.1007/978-3-662-44854-0_16
M3 - Article
SN - 0302-9743
VL - 8746
SP - 207
EP - 220
JO - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
JF - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ER -