TY - GEN
T1 - On musical score recognition using probabilistic reasoning
AU - Stückelberg, Marc Vuilleumier
AU - Doermann, David
N1 - Publisher Copyright:
© 1999 IEEE.
PY - 1999
Y1 - 1999
N2 - We present a probabilistic framework for document analysis and recognition and illustrate it on the problem of musical score recognition. Our system uses an explicit descriptive model of the document class to find the most likely interpretation of a scanned document image. In contrast to the traditional pipeline architecture, we carry out all stages of the analysis with a single inference engine, allowing for an end-to-end propagation of the uncertainty. The global modeling structure is similar to a stochastic attribute grammar, and local parameters are estimated using hidden Markov models.
AB - We present a probabilistic framework for document analysis and recognition and illustrate it on the problem of musical score recognition. Our system uses an explicit descriptive model of the document class to find the most likely interpretation of a scanned document image. In contrast to the traditional pipeline architecture, we carry out all stages of the analysis with a single inference engine, allowing for an end-to-end propagation of the uncertainty. The global modeling structure is similar to a stochastic attribute grammar, and local parameters are estimated using hidden Markov models.
UR - https://www.scopus.com/pages/publications/84951739259
U2 - 10.1109/ICDAR.1999.791738
DO - 10.1109/ICDAR.1999.791738
M3 - Conference contribution
AN - SCOPUS:84951739259
T3 - Proceedings of the International Conference on Document Analysis and Recognition, ICDAR
SP - 115
EP - 118
BT - Proceedings of the 5th International Conference on Document Analysis and Recognition, ICDAR 1999
PB - IEEE Computer Society
T2 - 5th International Conference on Document Analysis and Recognition, ICDAR 1999
Y2 - 20 September 1999 through 22 September 1999
ER -