Authors:
Artur Capela
1
;
Ana Rebelo
1
;
Jaime S. Cardoso
2
and
Carlos Guedes
3
Affiliations:
1
INESC Porto, Portugal
;
2
INESC Porto, Faculdade de Engenharia, Universidade do Porto, Portugal
;
3
INESC Porto, Escola Superior de Música e Artes do Espectáculo, Portugal
Keyword(s):
Music, optical character recognition, document image processing, image analysis.
Related
Ontology
Subjects/Areas/Topics:
Design and Implementation of Signal Processing Systems
;
Image and Video Processing, Compression and Segmentation
;
Multimedia
;
Multimedia Databases, Indexing, Recognition and Retrieval
;
Multimedia Signal Processing
;
Multimedia Systems and Applications
;
Telecommunications
Abstract:
Many music works produced in the past are currently available only as original manuscripts or as photocopies. Preserving them entails their digitalization and consequent accessibility in a machine-readable format, which encourages browsing, retrieval, search and analysis while providing a generalized access to the digital material. Carrying this task manually is very time consuming and error prone. While optical music recognition (OMR) systems usually perform well on printed scores, the processing of handwritten music by computers remains below the expectations. One of the fundamental stages to carry out this task is the detection and subsequent removal of staff lines. In this paper we integrate a general-purpose, knowledge-free method for the automatic detection of staff lines based on stable paths, into a recently developed staff line removal toolkit. Lines affected by curvature, discontinuities, and inclination are robustly detected. We have also developed a staff removal algorith
m adapting an existing line removal approach to use the stable path algorithm at the detection stage. Experimental results show that the proposed technique outperforms well-established algorithms. The developed algorithm will now be integrated in a web based system providing seamless access to browsing, retrieval, search and analysis of submitted scores.
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