Staff Line Removal Using Line Adjacency Graph and Staff Line Skeleton for Camera-Based Printed Music Scores

摘要

On camera-based music scores, curved and uneven staff-lines tend to incur more frequently, and with the loss in performance of binarization methods, line thickness variation and space variation between lines are inevitable. We propose a novel and effective staff-line removal method based on following 3 main ideas. First, the state-of-the-art staff-line detection method, Stable Path, is used to extract staff-line skeletons of the music score. Second, a line adjacency graph (LAG) model is exploited in a different manner of over segmentation to cluster pixel runs generated from the run-length encoding (RLE) of the image. Third, a two-pass staff-line removal pipeline called filament filtering is applied to remove clusters lying on the staff-line. Our method shows impressive results on music score images captured from cameras, and gives high performance when applied to the ICDAR/GREC 2013 database.