The ICDAR/GREC 2013 music scores competition: Staff removal

Alicia Fornés, Van Cuong Kieu, Muriel Visani, Nicholas Journet, Anjan Dutta

Research output: Contribution to journalArticleResearchpeer-review

8 Citations (Scopus)


© 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.
Original languageEnglish
Pages (from-to)207-220
JournalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Publication statusPublished - 1 Jan 2014


  • Competition
  • Graphics recognition
  • Music scores
  • Staff removal
  • Writer identification

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