PT Journal
AU Alicia Fornes
   Anjan Dutta
   Albert Gordo
   Josep Llados
TI CVC-MUSCIMA: A Ground-Truth of Handwritten Music Score Images for Writer Identification and Staff Removal
SO International Journal on Document Analysis and Recognition
JI IJDAR
PY 2012
BP 243
EP 251
VL 15
IS 3
DI 10.1007/s10032-011-0168-2
DE Music scores; Handwritten documents; Writer identification; Staff removal; Performance evaluation; Graphics recognition; Ground truths
AB 0,405JCRThe analysis of music scores has been an active research field in the last decades. However, there are no publicly available databases of handwritten music scores for the research community. In this paper we present the CVC-MUSCIMA database and ground-truth of handwritten music score images. The dataset consists of 1,000 music sheets written by 50 different musicians. It has been especially designed for writer identification and staff removal tasks. In addition to the description of the dataset, ground-truth, partitioning and evaluation metrics, we also provide some base-line results for easing the comparison between different approaches.
ER