TY - CHAP AU - Pau Riba AU - Alicia Fornes AU - Josep Llados ED - Bart Lamiroy ED - R Dueire Lins PY - 2017// TI - Towards the Alignment of Handwritten Music Scores T2 - LNCS BT - International Workshop on Graphics Recognition. GREC 2015.Graphic Recognition. Current Trends and Challenges SP - 103 EP - 116 VL - 9657 KW - Optical Music Recognition KW - Handwritten Music Scores KW - Dynamic Time Warping alignment N2 - It is very common to nd di erent versions of the same music work in archives of Opera Theaters. These di erences correspond to modi cations and annotations from the musicians. From the musicologist point of view, these variations are very interesting and deserve study.This paper explores the alignment of music scores as a tool for automatically detecting the passages that contain such di erences. Given the diculties in the recognition of handwritten music scores, our goal is to align the music scores and at the same time, avoid the recognition of music elements as much as possible. After removing the sta lines, braces and ties, the bar lines are detected. Then, the bar units are described as a whole using the Blurred Shape Model. The bar units alignment is performed by using Dynamic Time Warping. The analysis of the alignment path is used to detect the variations in the music scores. The method has been evaluated on a subset of the CVC-MUSCIMA dataset, showing encouraging results. SN - 978-3-319-52158-9 UR - https://link.springer.com/chapter/10.1007/978-3-319-52159-6_8 L1 - http://refbase.cvc.uab.es/files/RFL2017.pdf N1 - DAG; 600.097; 602.006; 600.121 ID - Pau Riba2017 ER -