A Comparative Survey of Image Binarisation Algorithms for Optical Recognition on Degraded Musical Sources

Abstract

Binarisation of greyscale images is a critical step in optical music recognition (OMR) preprocessing. Binarising music documents is particularly challenging because of the nature of music notation, even more so when the sources are degraded, e.g., with ink bleed-through from the other side of the page. This paper presents a comparative evaluation of 25 binarisation algorithms tested on a set of 100 music pages. A real-world OMR infrastructure for early music (Aruspix) was used to perform an objective, goaldirected evaluation of the algorithms’ performance. Our results differ significantly from the ones obtained in studies on non-music documents, which highlights the importance of developing tools specific to our community.