en
Proceedings chapter
Open access
English

On musical score recognition using probabilistic reasoning

Presented at 20-22 September 1999
Publication date1999
Abstract

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.

Citation (ISO format)
VUILLEUMIERSTUECKELBERG, Marc Christian, DOERMANN, David. On musical score recognition using probabilistic reasoning. In: ICDAR ’99 Proceedings of the Fifth International Conference on Document Analysis and Recognition. [s.l.] : [s.n.], 1999. p. 115.
Main files (1)
Proceedings chapter (Published version)
accessLevelPublic
Identifiers
  • PID : unige:121385
ISBN0-7695-0318-7
256views
131downloads

Technical informations

Creation07/23/2019 2:54:00 PM
First validation07/23/2019 2:54:00 PM
Update time03/15/2023 5:49:05 PM
Status update03/15/2023 5:49:04 PM
Last indexation01/17/2024 5:57:03 AM
All rights reserved by Archive ouverte UNIGE and the University of GenevaunigeBlack