A comparative study of staff removal algorithms.
This paper presents a quantitative comparison of different algorithms for the removal of stafflines from music images. It contains a survey of previously proposed algorithms and suggests a new skeletonization based approach. We define three different error metrics, compare the algorithms with respect to these metrics and measure their robustness with respect to certain image defects. Our test images are computer-generated scores on which we apply various image deformations typically found in real-world data. In addition to modern western music notation our test set also includes historic music notation such as mensural notation and lute tablature. Our general approach and evaluation methodology is not specific to staff removal, but applicable to other segmentation problems as well.
Dalitz
Christoph
C
Hochschule Niederrhein, Fachbereich Elektrotechnik und Informatik, Reinarzstr. 49, Krefeld, Germany. christoph.dalitz@hs-niederrhein.de
Droettboom
Michael
M
Pranzas
Bastian
B
Fujinaga
Ichiro
I
D000465:Algorithms; D001185:Artificial Intelligence; D004282:Documentation / Q000379:methods*; D001330:Electronic Data Processing / Q000379:methods*; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods; D009146:Music; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique