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A Comparative Study of Staff Removal Algorithms
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@MISC{Dalitz_acomparative,
author = {Christoph Dalitz and Michael Droettboom and Bastian Pranzas and Ichiro Fujinaga},
title = {A Comparative Study of Staff Removal Algorithms},
year = {}
}
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Abstract
Abstract — 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. Index Terms — Document page segmentation, OMR, performance evaluation, performance metric, pixel classification
Keyphrases
comparative study staff removal algorithm staff removal index term document page segmentation various image deformation pixel classification historic music notation real-world data different algorithm computer-generated score general approach music image segmentation problem test image western music notation performance evaluation test set evaluation methodology certain image defect lute tablature different error metric quantitative comparison new skeletonization mensural notation
