Optical music recognition (OMR) involves identifying musical symbols on a scanned sheet of music, and interpreting them so that the music can either be played by the computer, or put into a music editor. Applications include providing an automatic accompaniment, transposing or extracting parts for individual instruments, and performing an automated musicological analysis of the music. A key problem with music recognition, compared with character recognition, is that symbols very often overlap on the page. The most significant form of this problem is that the symbols are superimposed on a five-line staff. Although the staff provides valuable positional information, it creates ambiguity because it is difficult to determine whether a pixel would be black or white if the staff line was not there. The other main difference between music recognition and character recognition is the set of permissible symbols. In text, the alphabet size is fixed. Conversely, in music notation there is no standard "alphabet" of shapes, with composers inventing new notation where necessary, and music for particular instruments using specialised notation where appropriate. The focus of this paper is on techniques we have developed to deal with superimposed objects.
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