DocumentCode :
3485530
Title :
Staff Line Detection and Removal in the Grayscale Domain
Author :
Rebelo, A. ; Cardoso, Jaime S.
Author_Institution :
Fac. de Eng., Univ. do Porto, Porto, Portugal
fYear :
2013
fDate :
25-28 Aug. 2013
Firstpage :
57
Lastpage :
61
Abstract :
The detection of staff lines is the first step of most Optical Music Recognition (OMR) systems. Its great significance derives from the ease with which we can then proceed with the extraction of musical symbols. All OMR tasks are usually achieved using binary images by setting thresholds that can be local or global. These techniques however, may remove relevant information of the music sheet and introduce artifacts which will degrade results in the later stages of the process. It arises therefore a need to create a method that reduces the loss of information due to the binarization. The baseline for the methodology proposed in this paper follows the shortest path algorithm proposed in [CardosoTPAMI08]. The concept of strong staff pixels (SSP´s), which is a set of pixels with a high probability of belonging to a staff line, is proposed to guide the cost function. The SSP allows to overcome the results of the binary based detection and to generalize the binary framework to grayscale music scores. The proposed methodology achieves good results.
Keywords :
feature extraction; graph theory; music; object detection; optical character recognition; OMR systems; SSP; binary based detection; binary framework; binary images; cost function; global threshold; grayscale domain; grayscale music scores; local threshold; musical symbol extraction; optical music recognition system; shortest path algorithm; staff line detection; staff line removal; strong staff pixels; Cost function; Gray-scale; Image segmentation; Noise; Optical imaging; Robustness; Standards;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Document Analysis and Recognition (ICDAR), 2013 12th International Conference on
Conference_Location :
Washington, DC
ISSN :
1520-5363
Type :
conf
DOI :
10.1109/ICDAR.2013.20
Filename :
6628585
Link To Document :
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