TY  - JOUR
AU  - Alicia Fornes
AU  - Anjan Dutta
AU  - Albert Gordo
AU  - Josep Llados
PY  - 2012//
TI  - CVC-MUSCIMA: A Ground-Truth of Handwritten Music Score Images for Writer Identification and Staff Removal
T2  - IJDAR
JO  - International Journal on Document Analysis and Recognition
SP  - 243
EP  - 251
VL  - 15
IS  - 3
KW  - Music scores
KW  - Handwritten documents
KW  - Writer identification
KW  - Staff removal
KW  - Performance evaluation
KW  - Graphics recognition
KW  - Ground truths
N2  - 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.
SN  - 1433-2833
L1  - http://refbase.cvc.uab.es/files/FDG2012.pdf
UR  - http://dx.doi.org/10.1007/s10032-011-0168-2
N1  - DAG
ID  - Alicia Fornes2012
ER  -