Fast Lyric Area Extraction from Images of Printed Korean Music Scores

Abstract

In recent years, optical music recognition (OMR) has been extensively developed, particularly for use with mobile devices that require fast processing to recognize and play live the notes in images captured from sheet music. However, most techniques that have been developed thus far have focused on playing back instrumental music and have ignored the importance of lyric extraction, which is time consuming and affects the accuracy of the OMR tools. The text of the lyrics adds complexity to the page layout, particularly when lyrics touch or overlap musical symbols, in which case it is very difficult to separate them from each other. In addition, the distortion that appears in captured musical images makes the lyric lines curved or skewed, making the lyric extraction problem more complicated. This paper proposes a new approach in which lyrics are detected and extracted quickly and effectively. First, in order to resolve the distortion problem, the image is undistorted by a method using information of stave lines and bar lines. Then, through the use of a frequency count method and heuristic rules based on projection, the lyric areas are extracted, the cases where symbols touch the lyrics are resolved, and most of the information from the musical notation is kept even when the lyrics and music notes are overlapping. Our algorithm demonstrated a short processing time and remarkable accuracy on two test datasets of images of printed Korean musical scores: the first set included three hundred scanned musical images; the second set had two hundred musical images that were captured by a digital camera.